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What sets Laravel apart from other PHP web frameworks? Speed and simplicity, for starters. This rapid application development framework and its vast ecosystem of tools let you quickly build new sites and applications with clean, readable code. Fully updated to cover Laravel 5.8, the latest release, the second edition of ...
Laravel: Up & Running: A Framework for Building Modern PHP Apps
What sets Laravel apart from other PHP web frameworks? Speed and simplicity, for starters. This rapid application development framework and its vast ecosystem of tools let you quickly build new sites and applications with clean, readable code. Fully updated to cover Laravel 5.8, the latest release, the second edition of this practical guide provides the definitive introduction to one of today's most popular web frameworks. Matt Stauffer--a leading teacher and developer in the Laravel community--delivers a high-level overview and concrete examples to help experienced PHP web developers get started with Laravel right away. By the time you reach the last page, you should feel comfortable writing an entire application in Laravel from scratch.
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68.24 USD

Laravel: Up & Running: A Framework for Building Modern PHP Apps

by Matt Stauffer
Paperback / softback
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If you're just learning how to program, Julia is an excellent JIT-compiled, dynamically typed language with a clean syntax. This hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating ...
Think Julia: How to Think Like a Computer Scientist
If you're just learning how to program, Julia is an excellent JIT-compiled, dynamically typed language with a clean syntax. This hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch. Designed from the beginning for high performance, Julia is a general-purpose language ideal for not only numerical analysis and computational science but also web programming and scripting. Through exercises in each chapter, you'll try out programming concepts as you learn them. Think Julia is perfect for students at the high school or college level as well as self-learners and professionals who need to learn programming basics. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand types, methods, and multiple dispatch Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design and data structures through case studies
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68.24 USD

Think Julia: How to Think Like a Computer Scientist

by Allen B Downey, Ben Lauwens
Paperback / softback
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Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday developers, by providing a combination of tools such as cognitive services APIs, machine learning platforms, and libraries. Along with an overview of ...
Cognitive Computing Recipes: Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow
Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday developers, by providing a combination of tools such as cognitive services APIs, machine learning platforms, and libraries. Along with an overview of the contemporary technology landscape, Machine Learning and Deep Learning with Cognitive Computing Recipes covers the business case for machine learning and deep learning. Covering topics such as digital assistants, computer vision, text analytics, speech, and robotics process automation this book offers a comprehensive toolkit that you can apply quickly and easily in your own projects. With its focus on Microsoft Cognitive Services offerings, you'll see recipes using multiple different environments including TensowFlow and CNTK to give you a broader perspective of the deep learning ecosystem. What You Will Learn Build production-ready solutions using Microsoft Cognitive Services APIs Apply deep learning using TensorFlow and Microsoft Cognitive Toolkit (CNTK) Solve enterprise problems in natural language processing and computer vision Discover the machine learning development life cycle - from formal problem definition to deployment at scale Who This Book Is For Software engineers and enterprise architects who wish to understand machine learning and deep learning by building applications and solving real-world business problems.
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36.740000 USD

Cognitive Computing Recipes: Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow

by Adnan Hashmi, Adnan Masood
Paperback / softback
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Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to optimize your PySpark SQL ...
PySpark SQL Recipes: With HiveQL, Dataframe and Graphframes
Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to optimize your PySpark SQL code. PySpark SQL Recipes starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You'll also discover how to solve problems in graph analysis using graphframes. On completing this book, you'll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases. What You Will Learn Understand PySpark SQL and its advanced features Use SQL and HiveQL with PySpark SQL Work with structured streaming Optimize PySpark SQL Master graphframes and graph processing Who This Book Is ForData scientists, Python programmers, and SQL programmers.
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34.640000 USD

PySpark SQL Recipes: With HiveQL, Dataframe and Graphframes

by Sundar Rajan Raman, Raju Kumar Mishra
Paperback / softback
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Write high-level abstractions while retaining full control of the hardware, performances, and maintainability. Key Features Transform your ideas into modern C++ code, with both C++11 and C++17 Explore best practices for creating high-performance solutions Understand C++ basics and work with concrete real-world examples Book DescriptionC++ Fundamentals begins by introducing you ...
C++ Fundamentals: Hit the ground running with C++, the language that supports tech giants globally
Write high-level abstractions while retaining full control of the hardware, performances, and maintainability. Key Features Transform your ideas into modern C++ code, with both C++11 and C++17 Explore best practices for creating high-performance solutions Understand C++ basics and work with concrete real-world examples Book DescriptionC++ Fundamentals begins by introducing you to the C++ compilation model and syntax. You will then study data types, variable declaration, scope, and control flow statements. With the help of this book, you'll be able to compile fully working C++ code and understand how variables, references, and pointers can be used to manipulate the state of the program. Next, you will explore functions and classes - the features that C++ offers to organize a program - and use them to solve more complex problems. You will also understand common pitfalls and modern best practices, especially the ones that diverge from the C++98 guidelines. As you advance through the chapters, you'll study the advantages of generic programming and write your own templates to make generic algorithms that work with any type. This C++ book will guide you in fully exploiting standard containers and algorithms, understanding how to pick the appropriate one for each problem. By the end of this book, you will not only be able to write efficient code but also be equipped to improve the readability, performance, and maintainability of your programs. What you will learn C++ compilation model Apply best practices for writing functions and classes Write safe, generic, and efficient code with templates Explore the containers that the C++ standard offers Discover the new features introduced with C++11, C++14, and C++17 Get to grips with the core language features of C++ Solve complex problems using object-oriented programming in C++ Who this book is forIf you're a developer looking to learn a new powerful language or are familiar with C++ but want to update your knowledge with modern paradigms of C++11, C++14, and C++17, this book is for you. To easily understand the concepts in the book, you must be familiar with the basics of programming.
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31.490000 USD

C++ Fundamentals: Hit the ground running with C++, the language that supports tech giants globally

by Francesco Zoffoli, Antonio Mallia
Paperback / softback
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Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image ...
Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python
Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You'll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You'll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you'll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application. What You Will Learn Discover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects Who This Book Is For Data scientists and software developers interested in image processing and computer vision.
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36.740000 USD

Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python

by Himanshu Singh
Paperback / softback
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Property-based testing helps you create better, more solid tests with little code. By using the PropEr framework in both Erlang and Elixir, this book teaches you how to automatically generate test cases, test stateful programs, and change how you design your software for more principled and reliable approaches. You will ...
Property-Based Testing with PropEr, Erlang, and Eliixir
Property-based testing helps you create better, more solid tests with little code. By using the PropEr framework in both Erlang and Elixir, this book teaches you how to automatically generate test cases, test stateful programs, and change how you design your software for more principled and reliable approaches. You will be able to better explore the problem space, validate the assumptions you make when coming up with program behavior, and expose unexpected weaknesses in your design. PropEr will even show you how to reproduce the bugs it found. With this book, you will be writing efficient property-based tests in no time. Most tests only demonstrate that the code behaves how the developer expected it to behave, and therefore carry the same blind spots as their authors when special conditions or edge cases show up. Learn how to see things differently with property tests written in PropEr. Start with the basics of property tests, such as writing stateless properties, and using the default generators to generate test cases automatically. More importantly, learn how to think in properties. Improve your properties, write custom data generators, and discover what your code can or cannot do. Learn when to use property tests and when to stick with example tests with real-world sample projects. Explore various testing approaches to find the one that's best for your code. Shrink failing test cases to their simpler expression to highlight exactly what breaks in your code, and generate highly relevant data through targeted properties. Uncover the trickiest bugs you can think of with nearly no code at all with two special types of properties based on state transitions and finite state machines. Write Erlang and Elixir properties that generate the most effective tests you'll see, whether they are unit tests or complex integration and system tests. What You Need Basic knowledge of Erlang, optionally Elixir For Erlang tests: Erlang/OTP >= 20.0, with Rebar >= 3.4.0 For Elixir tests: Erlang/OTP >= 20.0, Elixir >= 1.5.0
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63.12 USD

Property-Based Testing with PropEr, Erlang, and Eliixir

by Fred Hebert
Paperback / softback
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Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You'll discover the ethical implications of healthcare data analytics and the future of ...
Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You'll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You'll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll Learn Gain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agents Who This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence - with the aim of improving patient health, population health and facilitating significant care-payer cost savings.
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39.890000 USD

Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes

by Arjun Panesar
Paperback / softback
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Leverage the power of the Unity 2018 game engine to create games with brilliant gameplay and high replayability. Key Features Develop different types of games from scratch with Unity 2018 Discover the secrets of creating AAA quality shaders without writing long algorithms Script intelligent game characters and agents using Artificial ...
Complete Unity 2018 Game Development: Explore techniques to build 2D/3D applications using real-world examples
Leverage the power of the Unity 2018 game engine to create games with brilliant gameplay and high replayability. Key Features Develop different types of games from scratch with Unity 2018 Discover the secrets of creating AAA quality shaders without writing long algorithms Script intelligent game characters and agents using Artificial Intelligence techniques and algorithms Book DescriptionThrough this Learning Path, you'll learn how to leverage the features of Unity and create amazing games, ranging from action shooters and mind-bending puzzle games to adventure and Virtual Reality(VR) games. If you have no prior experience of using Unity, you can still benefit from this Learning Path, which easily explains the complete working of the Unity toolset. You'll start by learning how to create compelling shaders using Unity and understanding everything you need to know about vectors. This includes useful inputs on how lighting is constructed with vectors and how textures are used to create complex effects without the need for advanced math. In the succeeding chapters, you'll also be able to use popular AI techniques, such as A* and A*mbush to develop intelligent pathfinding agents for your games. The book will also guide you through different algorithms for creating decision-making agents that go beyond simple behaviors and movement. By the end of this Learning Path, you will have developed all the basic skills to create highly engaging and replayable games. This Learning Path includes content from the following Packt products: Unity 2018 By Example - Second Edition by Alan Thorn Unity 2018 Shaders and Effects Cookbook - Third Edition by John P. Doran, Alan Zucconi Unity 2018 Artificial Intelligence Cookbook - Second Edition by Jorge Palacios What you will learn Understand concepts such as game objects, components, and scenes Create functional games with C# scripting Write shaders from scratch in ShaderLab and HLSL/Cg Develop intelligent pathfinding agents with A and Ambush Work with terrains and world-creation tools Simulate senses for agents to make decisions based on the environment Implement waypoints by creating a manual selector Enhance games with volumetric explosions, special effects, and visuals Who this book is forIf you are a game developer who wants to learn tools that can transform your gameplay, this beginner-level Learning Path is ideal for you. Having basic knowledge of C# will help you grasp the concepts explained in the book easily.
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52.490000 USD

Complete Unity 2018 Game Development: Explore techniques to build 2D/3D applications using real-world examples

by Jorge Palacios, Alan Zucconi, John P. Doran, Alan Thorn
Paperback / softback
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Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis. Natural Language Processing ...
Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python
Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis. Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You'll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing. By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient. What You Will Learn Apply NLP techniques using Python libraries such as NLTK, TextBlob, spaCy, Stanford CoreNLP, and many more Implement the concepts of information retrieval, text summarization, sentiment analysis, and other advanced natural language processing techniques. Identify machine learning and deep learning techniques for natural language processing and natural language generation problems Who This Book Is ForData scientists who want to refresh and learn various concepts of natural language processing through coding exercises.
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47.76 USD

Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python

by Adarsha Shivananda, Akshay Kulkarni
Paperback / softback
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There are only two mainstream solutions for building the graphical interface of Linux-based desktop applications, and GTK+ (GIMP Toolkit) is one of them. It is a necessary technology for all Linux programmers. This book guides the reader through the complexities of GTK+, laying the groundwork that allows the reader to ...
Foundations of PyGTK Development: GUI Creation with Python
There are only two mainstream solutions for building the graphical interface of Linux-based desktop applications, and GTK+ (GIMP Toolkit) is one of them. It is a necessary technology for all Linux programmers. This book guides the reader through the complexities of GTK+, laying the groundwork that allows the reader to make the leap from novice to professional. Beginning with an overview of key topics such as widget choice, placement, and behavior, readers move on to learn about more advanced issues. Replete with real-world examples, the developer can quickly take advantages of the concepts presented within to begin building his own projects.
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47.76 USD

Foundations of PyGTK Development: GUI Creation with Python

by Andrew Krause, W. David Ashley
Paperback / softback
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This updated edition of Java in a Nutshell not only helps experienced Java programmers get the most out of Java versions 9 through 11, it's also a learning path for new developers. Chock full of examples that demonstrate how to take complete advantage of modern Java APIs and development best ...
Java in a Nutshell 7e
This updated edition of Java in a Nutshell not only helps experienced Java programmers get the most out of Java versions 9 through 11, it's also a learning path for new developers. Chock full of examples that demonstrate how to take complete advantage of modern Java APIs and development best practices, this thoroughly revised book includes new material on Java Concurrency Utilities. The book's first section provides a fast-paced, no-fluff introduction to the Java programming language and the core runtime aspects of the Java platform. The second section is a reference to core concepts and APIs that explains how to perform real programming work in the Java environment. Get up to speed on language details, including Java 9-11 changes Learn object-oriented programming, using basic Java syntax Explore generics, enumerations, annotations, and lambda expressions Understand basic techniques used in object-oriented design Examine concurrency and memory, and how they're intertwined Work with Java collections and handle common data formats Delve into Java's latest I/O APIs, including asynchronous channels Use Nashorn to execute JavaScript on the Java Virtual Machine Become familiar with development tools in OpenJDK
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81.89 USD

Java in a Nutshell 7e

by David Flanagan, Ben Evans
Paperback / softback
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Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along with natural language processing and recommender systems using PySpark. ...
Machine Learning with PySpark: With Natural Language Processing and Recommender Systems
Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along with natural language processing and recommender systems using PySpark. Machine Learning with PySpark shows you how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forest. You'll also see unsupervised machine learning models such as K-means and hierarchical clustering. A major portion of the book focuses on feature engineering to create useful features with PySpark to train the machine learning models. The natural language processing section covers text processing, text mining, and embedding for classification. After reading this book, you will understand how to use PySpark's machine learning library to build and train various machine learning models. Additionally you'll become comfortable with related PySpark components, such as data ingestion, data processing, and data analysis, that you can use to develop data-driven intelligent applications. What You Will Learn Build a spectrum of supervised and unsupervised machine learning algorithms Implement machine learning algorithms with Spark MLlib libraries Develop a recommender system with Spark MLlib libraries Handle issues related to feature engineering, class balance, bias and variance, and cross validation for building an optimal fit model Who This Book Is For Data science and machine learning professionals.
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39.23 USD

Machine Learning with PySpark: With Natural Language Processing and Recommender Systems

by Pramod Singh
Paperback / softback
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Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical ...
Practical Apache Spark: Using the Scala API
Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You'll follow a learn-to-do-by-yourself approach to learning - learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure. On completion, you'll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You'll also become familiar with machine learning algorithms with real-time usage. What You Will Learn Discover the functional programming features of Scala Understand the complete architecture of Spark and its components Integrate Apache Spark with Hive and Kafka Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries Work with different machine learning concepts and libraries using Spark's MLlib packages Who This Book Is For Developers and professionals who deal with batch and stream data processing.
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47.240000 USD

Practical Apache Spark: Using the Scala API

by Dharanitharan Ganesan, Subhashini Chellappan
Paperback / softback
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Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus ...
Machine Learning Using R: With Time Series and Industry-Based Use Cases in R
Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python if you are only comfortable with R. As in the first edition, the authors have kept the fine balance of theory and application of machine learning through various real-world use-cases which gives you a comprehensive collection of topics in machine learning. New chapters in this edition cover time series models and deep learning. What You'll Learn Understand machine learning algorithms using R Master the process of building machine-learning models Cover the theoretical foundations of machine-learning algorithms See industry focused real-world use cases Tackle time series modeling in R Apply deep learning using Keras and TensorFlow in R Who This Book is For Data scientists, data science professionals, and researchers in academia who want to understand the nuances of machine-learning approaches/algorithms in practice using R.
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41.990000 USD

Machine Learning Using R: With Time Series and Industry-Based Use Cases in R

by Abhishek Singh, Karthik Ramasubramanian
Paperback / softback
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Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you'll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only ...
Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance
Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you'll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You'll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. What You Will Learn Discover applied machine learning processes and principles Implement machine learning in areas of healthcare, finance, and retail Avoid the pitfalls of implementing applied machine learning Build Python machine learning examples in the three subject areas Who This Book Is For Data scientists and machine learning professionals.
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56.29 USD

Machine Learning Applications Using Python: Cases Studies from Healthcare, Retail, and Finance

by Puneet Mathur
Paperback / softback
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Dive deep into Jenkins Blue Ocean and discover how easy creating a pipeline can be. You'll see how Blue Ocean provides a better user experience when designing, running, and visualizing pipelines. This book shows you its intuitive user interface and its powerful pipeline editor and how this makes it a ...
Beginning Jenkins Blue Ocean: Create Elegant Pipelines With Ease
Dive deep into Jenkins Blue Ocean and discover how easy creating a pipeline can be. You'll see how Blue Ocean provides a better user experience when designing, running, and visualizing pipelines. This book shows you its intuitive user interface and its powerful pipeline editor and how this makes it a tool for everyone. Beginning Jenkins Blue Ocean starts with an introduction to Blue Ocean, followed by a step-by-step guide on how to set it up. You'll learn how to create a pipeline for every branch and pull request on your Git, GitHub, and GitLab repositories. You'll experience the improved pipeline visualization and log diagnosis features in Blue Ocean. Later you will go beyond the visual pipeline editor to learn the declarative syntax and gain better control over your pipelines. Then, you'll take a look at some tools to enable you to write pipeline code in the declarative syntax. You will also learn to extend delivery pipelines with Jenkins shared libraries. What You Will Learn Discover Jenkins Blue Ocean and how to use it Create elegant pipelines using the visual pipeline editor Work with the declarative pipeline syntax Use tools that help you write declarative pipeline code Extend pipelines with Jenkins shared libraries Visualize pipelines from classic Jenkins in Blue Ocean Configure and view test results in Blue Ocean Accurately diagnose pipeline failures using improved pipeline visualization Create multibranch pipeline projects for your Git, GitHub, and GitLab repositories Who This Book Is For Those new to Jenkins who are looking for an easy introduction. The book will also be useful for readers familiar with classic Jenkins and would like to learn Jenkins Blue Ocean.
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34.640000 USD

Beginning Jenkins Blue Ocean: Create Elegant Pipelines With Ease

by Nikhil Pathania
Paperback / softback
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Mitigate the risks involved in migrating away from a proprietary database platform toward MariaDB's open source database engine. This book will help you assess the risks and the work involved, and ensure a successful migration. Migrating to MariaDB describes the process and lessons learned during a migration from a proprietary ...
Migrating to MariaDB: Toward an Open Source Database Solution
Mitigate the risks involved in migrating away from a proprietary database platform toward MariaDB's open source database engine. This book will help you assess the risks and the work involved, and ensure a successful migration. Migrating to MariaDB describes the process and lessons learned during a migration from a proprietary database management engine to the MariaDB open source solution. The book discusses the drivers for making the decision and change, walking you through all aspects of the process from evaluating the licensing, navigating the pitfalls and hurdles of a migration, through to final implementation on the new platform. The book highlights the cost-effectiveness of MariaDB and how the licensing worries are simplified in comparison to running on a proprietary platform. You'll learn to do your own risk assessment, to identify database and application code that may need to be modified or re-implemented, and to identify MariaDB features to provide the security and failover protection needed by corporate customers. Let the author's experience in migrating a financial firm to MariaDB inform your own efforts, helping you to develop a road map for both technical and political success within your own organization as you migrate away from proprietary lock-in toward MariaDB's open source solution. What You'll Learn Evaluate and compare licensing costs between proprietary databases and MariaDB Perform a proper risk assessment to inform your planning and execution of the migration Build a migration road map from the book's example that is specific to your situation Make needed application changes and migrate data to the MariaDB open source database engine Who This Book Is For Technical professionals (including database administrators, programmers, and technical management) who are interested in migrating away from a proprietary database platform toward MariaDB's open source database engine and need to assess the risks and the work involved
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39.890000 USD

Migrating to MariaDB: Toward an Open Source Database Solution

by William Wood
Paperback / softback
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Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in ...
Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python
Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You'll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you'll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras. What You'll Learn Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions. Design, develop, train, validate, and deploy deep neural networks using the Keras framework Use best practices for debugging and validating deep learning models Deploy and integrate deep learning as a service into a larger software service or product Extend deep learning principles into other popular frameworks Who This Book Is For Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.
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34.640000 USD

Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

by Jojo Moolayil
Paperback / softback
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Learn about bot programming, using all the latest and greatest programming languages, including Python, Go, and Clojure, so you can feel at ease writing your Telegram bot in a way that suits you. This book shows how you can use bots for just about everything: they connect, they respond, they ...
Building Telegram Bots: Develop Bots in 12 Programming Languages using the Telegram Bot API
Learn about bot programming, using all the latest and greatest programming languages, including Python, Go, and Clojure, so you can feel at ease writing your Telegram bot in a way that suits you. This book shows how you can use bots for just about everything: they connect, they respond, they enhance your job search chances, they do technical research for you, they remind you about your last train, they tell the difference between a horse and a zebra, they can tell jokes, and they can cheer you up in the middle of the night. Bots used to be hard to set up and enhance, but with the help of Building Telegram Bots you'll see how the Telegram platform is now making bot creation easier than ever. You will begin by writing a simple bot at the start and then gradually build upon it. The simple yet effective Telegram Bot API makes it very easy to develop bots in a number of programming languages. Languages featured in the book include Node.js, Java, Rust, and Elixir. This book encourages you to not only learn the basic process of creating a bot but also lets you spend time exploring its possibilities. By the end of the book you will be able create your own Telegram Bot with the programming language of your choice. What You Will Learn Carry out simple bot design and deployment in various programming languages including Ruby, D, Crystal, Nim, and C++ Create engaging bot interactions with your users Add payments and media capabilities to your bots Master programming language abstraction Who This Book Is For Engineers who want to get things done. People who are curious. Programming beginners. Advanced engineers with little time to do research.
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39.890000 USD

Building Telegram Bots: Develop Bots in 12 Programming Languages using the Telegram Bot API

by Nicolas Modrzyk
Paperback / softback
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Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover ...
Practical Computer Vision Applications Using Deep Learning with CNNs: With Detailed Examples in Python Using TensorFlow and Kivy
Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the convolutional neural network (CNN) deep learning model and Python. This book starts by explaining the traditional machine-learning pipeline, where you will analyze an image dataset. Along the way you will cover artificial neural networks (ANNs), building one from scratch in Python, before optimizing it using genetic algorithms. For automating the process, the book highlights the limitations of traditional hand-crafted features for computer vision and why the CNN deep-learning model is the state-of-art solution. CNNs are discussed from scratch to demonstrate how they are different and more efficient than the fully connected ANN (FCNN). You will implement a CNN in Python to give you a full understanding of the model. After consolidating the basics, you will use TensorFlow to build a practical image-recognition model that you will deploy to a web server using Flask, making it accessible over the Internet. Using Kivy and NumPy, you will create cross-platform data science applications with low overheads. This book will help you apply deep learning and computer vision concepts from scratch, step-by-step from conception to production. What You Will Learn Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using Python Follow a deep learning project from conception to production using TensorFlow Use NumPy with Kivy to build cross-platform data science applications Who This Book Is ForData scientists, machine learning and deep learning engineers, software developers.
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56.29 USD

Practical Computer Vision Applications Using Deep Learning with CNNs: With Detailed Examples in Python Using TensorFlow and Kivy

by Ahmed Fawzy Gad
Paperback / softback
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Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R's syntax, you will work through ...
Learn R for Applied Statistics: With Data Visualizations, Regressions, and Statistics
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R's syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will Learn Discover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.
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39.890000 USD

Learn R for Applied Statistics: With Data Visualizations, Regressions, and Statistics

by Eric Goh Ming Hui
Paperback / softback
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Get started in white-hat ethical hacking using Kali Linux. This book starts off by giving you an overview of security trends, where you will learn the OSI security architecture. This will form the foundation for the rest of Beginning Ethical Hacking with Kali Linux. With the theory out of the ...
Beginning Ethical Hacking with Kali Linux: Computational Techniques for Resolving Security Issues
Get started in white-hat ethical hacking using Kali Linux. This book starts off by giving you an overview of security trends, where you will learn the OSI security architecture. This will form the foundation for the rest of Beginning Ethical Hacking with Kali Linux. With the theory out of the way, you'll move on to an introduction to VirtualBox, networking, and common Linux commands, followed by the step-by-step procedure to build your own web server and acquire the skill to be anonymous . When you have finished the examples in the first part of your book, you will have all you need to carry out safe and ethical hacking experiments. After an introduction to Kali Linux, you will carry out your first penetration tests with Python and code raw binary packets for use in those tests. You will learn how to find secret directories on a target system, use a TCP client in Python, and scan ports using NMAP. Along the way you will discover effective ways to collect important information, track email, and use important tools such as DMITRY and Maltego, as well as take a look at the five phases of penetration testing. The coverage of vulnerability analysis includes sniffing and spoofing, why ARP poisoning is a threat, how SniffJoke prevents poisoning, how to analyze protocols with Wireshark, and using sniffing packets with Scapy. The next part of the book shows you detecting SQL injection vulnerabilities, using sqlmap, and applying brute force or password attacks. Besides learning these tools, you will see how to use OpenVas, Nikto, Vega, and Burp Suite. The book will explain the information assurance model and the hacking framework Metasploit, taking you through important commands, exploit and payload basics. Moving on to hashes and passwords you will learn password testing and hacking techniques with John the Ripper and Rainbow. You will then dive into classic and modern encryption techniques where you will learn the conventional cryptosystem. In the final chapter you will acquire the skill of exploiting remote Windows and Linux systems and you will learn how to own a target completely. What You Will Learn Master common Linux commands and networking techniques Build your own Kali web server and learn to be anonymous Carry out penetration testing using Python Detect sniffing attacks and SQL injection vulnerabilities Learn tools such as SniffJoke, Wireshark, Scapy, sqlmap, OpenVas, Nikto, and Burp Suite Use Metasploit with Kali Linux Exploit remote Windows and Linux systems Who This Book Is For Developers new to ethical hacking with a basic understanding of Linux programming.
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41.990000 USD

Beginning Ethical Hacking with Kali Linux: Computational Techniques for Resolving Security Issues

by Sanjib Sinha
Paperback / softback
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Learn to view, edit and analyse geospatial data using QGIS and Python 3 Key Features Leverage the power of QGIS to add professionalism to your maps Explore and work with the newly released features like Python 3, GeoPackage, 3D views, Print layouts in QGIS 3.4 Build your own plugins and ...
Learn QGIS: Your step-by-step guide to the fundamental of QGIS 3.4, 4th Edition
Learn to view, edit and analyse geospatial data using QGIS and Python 3 Key Features Leverage the power of QGIS to add professionalism to your maps Explore and work with the newly released features like Python 3, GeoPackage, 3D views, Print layouts in QGIS 3.4 Build your own plugins and customize maps using QT designer Book DescriptionQGIS 3.4 is the first LTR (long term release) of QGIS version 3. This is a giant leap forward for the project with tons of new features and impactful changes. Learn QGIS is fully updated for QGIS 3.4, covering its processing engine update, Python 3 de-facto coding environment, and the GeoPackage format. This book will help you get started on your QGIS journey, guiding you to develop your own processing pathway. You will explore the user interface, loading your data, editing, and then creating data. QGIS often surprises new users with its mapping capabilities; you will discover how easily you can style and create your first map. But that's not all! In the final part of the book, you'll learn about spatial analysis and the powerful tools in QGIS, and conclude by looking at Python processing options. By the end of the book, you will have become proficient in geospatial analysis using QGIS and Python. What you will learn Explore various ways to load data into QGIS Understand how to style data and present it in a map Create maps and explore ways to expand them Get acquainted with the new processing toolbox in QGIS 3.4 Manipulate your geospatial data and gain quality insights Understand how to customize QGIS 3.4 Work with QGIS 3.4 in 3D Who this book is forIf you are a developer or consultant familiar with the basic functions and processes of GIS and want to learn how to use QGIS to analyze geospatial data and create rich mapping applications, this book is for you. You'll also find this book useful if you're new to QGIS and wish to grasp its fundamentals
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41.990000 USD

Learn QGIS: Your step-by-step guide to the fundamental of QGIS 3.4, 4th Edition

by Anita Graser, Andrew Cutts
Paperback / softback
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Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as ...
Data Analysis and Visualization Using Python: Analyze Data to Create Visualizations for BI Systems
Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python. Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python. In conclusion, you will complete a detailed case study, where you'll get a chance to revisit the concepts you've covered so far. What You Will Learn Use Python programming techniques for data science Master data collections in Python Create engaging visualizations for BI systems Deploy effective strategies for gathering and cleaning data Integrate the Seaborn and Matplotlib plotting systems Who This Book Is For Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.
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41.990000 USD

Data Analysis and Visualization Using Python: Analyze Data to Create Visualizations for BI Systems

by Dr. Ossama Embarak
Paperback / softback
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While Kubernetes has greatly simplified the task of deploying containerized applications, managing this orchestration framework on a daily basis can still be a complex undertaking. With this practical book, site reliability and DevOps engineers will learn how to build, operate, manage, and upgrade a Kubernetes cluster-whether it resides on cloud ...
Managing Kubernetes
While Kubernetes has greatly simplified the task of deploying containerized applications, managing this orchestration framework on a daily basis can still be a complex undertaking. With this practical book, site reliability and DevOps engineers will learn how to build, operate, manage, and upgrade a Kubernetes cluster-whether it resides on cloud infrastructure or on-premises. Brendan Burns, cofounder of Kubernetes, and Craig Tracey, staff field engineer at Heptio, dissect how Kubernetes works internally and demonstrate ways to maintain, adjust, and improve the cluster to suit your particular use case. You'll learn how to make architectural choices for designing a cluster, managing access control, monitoring and alerting, and upgrading Kubernetes. Dive in and discover how to take full advantage of this orchestration framework's capabilities. Learn how your cluster operates, how developers use it to deploy applications, and how Kubernetes can facilitate a developer's job Adjust, secure, and tune your cluster by understanding Kubernetes APIs and configuration options Detect cluster-level problems early and learn the steps necessary to respond and recover quickly Determine how and when to add libraries, tools, and platforms that build on, extend, or otherwise improve a Kubernetes cluster
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61.41 USD

Managing Kubernetes

by Craig Tracey, Brendan Burns
Paperback / softback
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Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such ...
Learning Apache Drill: Query and Analyze Distributed Data Sources with SQL
Get up to speed with Apache Drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as Parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such as HBase, MongoDB, and relational databases. Drill works everywhere: on your laptop or in your largest cluster. In this practical book, Drill committers Charles Givre and Paul Rogers show analysts and data scientists how to query and analyze raw data using this powerful tool. Data scientists today spend about 80% of their time just gathering and cleaning data. With this book, you'll learn how Drill helps you analyze data more effectively to drive down time to insight. Use Drill to clean, prepare, and summarize delimited data for further analysis Query file types including logfiles, Parquet, JSON, and other complex formats Query Hadoop, relational databases, MongoDB, and Kafka with standard SQL Connect to Drill programmatically using a variety of languages Use Drill even with challenging or ambiguous file formats Perform sophisticated analysis by extending Drill's functionality with user-defined functions Facilitate data analysis for network security, image metadata, and machine learning
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81.89 USD

Learning Apache Drill: Query and Analyze Distributed Data Sources with SQL

by Paul Rogers, Charles Givre
Paperback / softback
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Apply design principles to your classes, preparing them for reuse. You will use package design principles to create packages that are just right in terms of cohesion and coupling, and are user- and maintainer-friendly at the same time. The first part of this book walks you through the five SOLID ...
Principles of Package Design: Creating Reusable Software Components
Apply design principles to your classes, preparing them for reuse. You will use package design principles to create packages that are just right in terms of cohesion and coupling, and are user- and maintainer-friendly at the same time. The first part of this book walks you through the five SOLID principles that will help you improve the design of your classes. The second part introduces you to the best practices of package design, and covers both package cohesion principles and package coupling principles. Cohesion principles show you which classes should be put together in a package, when to split packages, and if a combination of classes may be considered a package in the first place. Package coupling principles help you choose the right dependencies and prevent wrong directions in the dependency graph of your packages. What You'll Learn Apply the SOLID principles of class design Determine if classes belong in the same package Know whether it is safe for packages to depend on each other Who This Book Is For Software developers with a broad range of experience in the field, who are looking for ways to reuse,share, and distribute their code
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47.240000 USD

Principles of Package Design: Creating Reusable Software Components

by Matthias Noback
Paperback / softback
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Discover how a software engineer can leverage Docker in order to expedite development velocity. This book focuses on the fundamental concepts this program is built upon and explores how it can help you get your services up and running inside Docker containers. You'll also review tips on how to debug ...
Accelerating Development Velocity Using Docker: Docker Across Microservices
Discover how a software engineer can leverage Docker in order to expedite development velocity. This book focuses on the fundamental concepts this program is built upon and explores how it can help you get your services up and running inside Docker containers. You'll also review tips on how to debug microservices applications that run inside Docker containers. Tech companies are now developing complex softwares that are comprised of multiple services running on different platforms, and Docker has become an essential part of coordinating the communication between these services and platforms. This book addresses problems caused by drifting microservices, debugging across services, inconsistent environments across machines, and coordinating development of machine learning systems between a team of developers, etc. Accelerating Development Velocity Using Docker puts you on the path to transforming your complex systems into more efficient ones. What You'll Learn Setup Docker and employ quick solutions to road blocks Review challenges associated with debugging microservices that sit behind a complex application Leverage Docker features to seamlessly get multiple microservices up and running Debug inside a Docker container Review advanced use cases of Docker that can help consistency of development environments* Who This Book Is For Ideal for new to mid-level infrastructure engineers who want to learn how to make their development environments efficient across their and cross teams, or for students who aspire to learn basics of how to debug distributed systems and how to develop efficient applications.
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34.640000 USD

Accelerating Development Velocity Using Docker: Docker Across Microservices

by Kinnary Jangla
Paperback / softback
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If you're grounded in the basics of Swift, Xcode, and the Cocoa framework, this book provides a structured explanation of all essential real-world iOS app components. Through deep exploration and copious code examples, you'll learn how to create views, manipulate view controllers, and add features from iOS frameworks. Create, arrange, ...
Programming iOS 12: Dive Deep into Views, View Controllers, and Frameworks
If you're grounded in the basics of Swift, Xcode, and the Cocoa framework, this book provides a structured explanation of all essential real-world iOS app components. Through deep exploration and copious code examples, you'll learn how to create views, manipulate view controllers, and add features from iOS frameworks. Create, arrange, draw, layer, and animate views that respond to touch Use view controllers to manage multiple screens of interface Master interface classes for scroll views, table views, text, popovers, split views, web views, and controls Dive into frameworks for sound, video, maps, and sensors Access user libraries: music, photos, contacts, and calendar Explore additional topics, including files, networking, and threads Stay up-to-date on iOS 12 innovations, such as User Notification framework improvements, as well as changes in Xcode 10 and Swift 4.2. All example code is available on GitHub for you to download, study, and run. Want to brush up on the basics? Pick up iOS 12 Programming Fundamentals with Swift to learn about Swift, Xcode, and Cocoa. Together with Programming iOS 12, you'll gain a solid, rigorous, and practical understanding of iOS 12 development.
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95.54 USD

Programming iOS 12: Dive Deep into Views, View Controllers, and Frameworks

by Matt Neuberg
Paperback / softback
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