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Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a ...
Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks-including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively into deep learning theory so that by the end of the book you'll have a complete understanding of the math behind the library's functions.
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73.490000 USD

Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD

by Jeremy Howard, Sylvain Gugger
Paperback / softback
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Apply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python. The case study section starts with ...
IoT Machine Learning Applications in Telecom, Energy, and Agriculture: With Raspberry Pi and Arduino Using Python
Apply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python. The case study section starts with an examination of call drop with IoT in the telecoms industry, followed by a case study on energy audit and predictive maintenance for an industrial machine, and finally covers techniques to predict cash crop failure in agribusiness. The last section covers pitfalls to avoid while implementing machine learning and IoT in these domains. After reading this book, you will know how IoT and machine learning are used in the example domains and have practical case studies to use and extend. You will be able to create enterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python. What You Will Learn Implement machine learning with IoT and solve problems in the telecom, agriculture, and energy sectors with Python Set up and use industrial-grade IoT products, such as Modbus RS485 protocol devices, in practical scenarios Develop solutions for commercial-grade IoT or IIoT projects Implement case studies in machine learning with IoT from scratch Who This Book Is For Raspberry Pi and Arduino enthusiasts and data science and machine learning professionals.
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36.740000 USD

IoT Machine Learning Applications in Telecom, Energy, and Agriculture: With Raspberry Pi and Arduino Using Python

by Puneet Mathur
Paperback / softback
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As Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are now taking an interest in high-level software architecture patterns such as hexagonal/clean architecture, event-driven architecture, and strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn't always straightforward. ...
Enterprise Architecture Patterns with Python: How to Apply DDD, Ports and Adapters, and Enterprise Architecture Design Patterns in a Pythonic Way
As Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are now taking an interest in high-level software architecture patterns such as hexagonal/clean architecture, event-driven architecture, and strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn't always straightforward. With this practical guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity. Each pattern is illustrated with concrete examples in idiomatic Python that explain how to avoid some of the unnecessary verbosity of Java and C# syntax. You'll learn how to implement each of these patterns in a Pythonic way. Architectural design patterns include: Dependency inversion, and its links to ports and adapters (hexagonal/clean architecture) Domain-driven design's distinction between entities, value objects, and aggregates Repository and Unit of Work patterns for persistent storage Events, commands, and the message bus Command Query Responsibility Segregation (CQRS) Event-driven architecture and reactive microservices
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89.25 USD

Enterprise Architecture Patterns with Python: How to Apply DDD, Ports and Adapters, and Enterprise Architecture Design Patterns in a Pythonic Way

by Bob Gregory, Harry J.W. Percival
Paperback / softback
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If you're among the Python developers put off by Asyncio's complexity, it's time to take another look. Asyncio is complicated because it aims to solve problems in concurrent network programming for both framework developers and end-user developers like you. The features you need to consider are a small subset of ...
Using Asyncio in Python: Understanding Python's Asynchronous Programming Features
If you're among the Python developers put off by Asyncio's complexity, it's time to take another look. Asyncio is complicated because it aims to solve problems in concurrent network programming for both framework developers and end-user developers like you. The features you need to consider are a small subset of the whole Asyncio API, but picking out the right features is the tricky part. That's where this practical book comes in. Veteran Python developer Caleb Hattingh helps end-user developers gain a basic understanding of Asyncio's building blocks-enough to get you started writing simple event-based programs. You'll learn why Asyncio offers a safer alternative to preemptive multitasking (threading) and how this API provides a simple way to support thousands of simultaneous socket connections. Get a critical comparison of Asyncio and threading for concurrent network programming Take an Asyncio walkthrough, including a quickstart guide to help you hit the ground looping with event-based programming Learn the difference between Asyncio features for end-user developers and those for framework developers Understand Asyncio's new async/await language syntax, including coroutines and task and future APIs Get detailed case studies (with code) of some popular Asyncio-compatible third-party libraries
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47.240000 USD

Using Asyncio in Python: Understanding Python's Asynchronous Programming Features

by Caleb Hattingh
Paperback / softback
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With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You'll get familiar with Python's functional built-ins like the functools operator and itertools modules, as well as the toolz library. Mastering Large Datasets teaches you to write easily ...
Mastering Large Datasets: Parallelize and Distribute Your Python Code
With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You'll get familiar with Python's functional built-ins like the functools operator and itertools modules, as well as the toolz library. Mastering Large Datasets teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data. By the end of this comprehensive guide, you'll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level! Key features * An introduction to functional and parallel programming * Data science workflow * Profiling code for better performance * Fulfilling different quality objectives for a single unifying task * Python multiprocessing * Practical exercises including full-scale distributed applications Audience Readers should have intermediate Python programming skills. About the technology Python is a data scientist's dream-come-true, thanks to readily available libraries that support tasks like data analysis, machine learning, visualization, and numerical computing. J.T. Wolohan is a lead data scientist at Booz Allen Hamilton and a PhD researcher at Indiana University, Bloomington, affiliated with the Department of Information and Library Science and the School of Informatics and Computing. His professional work focuses on rapid prototyping and scalable AI. His research focuses on computational analysis of social uses of language online.
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52.490000 USD

Mastering Large Datasets: Parallelize and Distribute Your Python Code

by John T. Wolohan
Paperback / softback
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Practices of the Python Pro teaches you to design and write software that's easy to understand, maintain, and scale. Using practical Python-based examples, experienced developer Dane Hillard introduces design concepts that lay the foundation for designing, building, and maintaining software that's good for the long haul. You'll learn established guidelines ...
Practices of the Python Pro
Practices of the Python Pro teaches you to design and write software that's easy to understand, maintain, and scale. Using practical Python-based examples, experienced developer Dane Hillard introduces design concepts that lay the foundation for designing, building, and maintaining software that's good for the long haul. You'll learn established guidelines for clean coding style and explore techniques to address design considerations like speed, integrity, security, and extensibility. Organizing large Python projects Leveraging abstraction for clean code Writing flexible, reusable code Inheritance and composition Considerations for testing and performance
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41.990000 USD

Practices of the Python Pro

by Dane Hillard
Paperback / softback
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Hello World! Third Edition is a fun, easy-to-use guide with copious illustrations and engaging examples. It takes the reader on a playful tour of basic programming concepts and then puts those concepts together to make fun and useful programs. It uses Python, a programming language that is one of the ...
Hello World!
Hello World! Third Edition is a fun, easy-to-use guide with copious illustrations and engaging examples. It takes the reader on a playful tour of basic programming concepts and then puts those concepts together to make fun and useful programs. It uses Python, a programming language that is one of the easiest to read, write, and understand. Like the previous two editions, Hello World! Third Edition is not just for kids. While the tone is light and engaging, it doesn't talk down to the reader, and beginners of any age will love its readability and sense of humor. Written by Warren Sande and his son, Carter, it is full of examples that will get you thinking and learning. Reviewed by professional educators, this book is kid-tested and parent-approved. You don't need to know anything about programming to use the book, just the basics of using a computer. If you can start a program and save a file, you can learn to program using this book! Uses free open source software Lots of graphics, cartoons, and fun examples Complete set of practice questions and exercises Illustrated in full color
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41.990000 USD

Hello World!

by Carter Sande, Warren Sande
Paperback / softback
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Updated and Expanded for Python 3 It's easy to start developing programs with Python, which is why the language is so popular. However, Python's unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. This second edition of Effective ...
Effective Python: 90 Specific Ways to Write Better Python
Updated and Expanded for Python 3 It's easy to start developing programs with Python, which is why the language is so popular. However, Python's unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. This second edition of Effective Python will help you master a truly Pythonic approach to programming, harnessing Python's full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers' best-selling Effective C++, Brett Slatkin brings together 90 Python best practices, tips, and shortcuts, and explains them with realistic code examples so that you can embrace Python with confidence. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You'll understand the best way to accomplish key tasks so you can write code that's easier to understand, maintain, and improve. In addition to even more advice, this new edition substantially revises all items from the first edition to reflect how best practices have evolved. Key features include 30 new actionable guidelines for all major areas of Python Detailed explanations and examples of statements, expressions, and built-in types Best practices for writing functions that clarify intention, promote reuse, and avoid bugs Better techniques and idioms for using comprehensions and generator functions Coverage of how to accurately express behaviors with classes and interfaces Guidance on how to avoid pitfalls with metaclasses and dynamic attributes More efficient and clear approaches to concurrency and parallelism Solutions for optimizing and hardening to maximize performance and quality Techniques and built-in modules that aid in debugging and testing Tools and best practices for collaborative development Effective Python will prepare growing programmers to make a big impact using Python.
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70.65 USD

Effective Python: 90 Specific Ways to Write Better Python

by Brett Slatkin
Paperback / softback
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Python for DevOps shows you how to harness Python for everyday Linux systems administration tasks, as well as today's most useful devops tools, including Docker, Kubernetes, and Terraform. Embrace automation and you'll never look at a boring task the same way again.
Python for DevOps: Learn Ruthlessly Effective Automation
Python for DevOps shows you how to harness Python for everyday Linux systems administration tasks, as well as today's most useful devops tools, including Docker, Kubernetes, and Terraform. Embrace automation and you'll never look at a boring task the same way again.
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62.990000 USD

Python for DevOps: Learn Ruthlessly Effective Automation

by Grig Gherghiu, Robert Jordan, Alfredo Deza, Kennedy Behrman, Noah Gift
Paperback / softback
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Immerse yourself in learning Python and introductory data analytics with this book's project-based approach. Through the structure of a ten-week coding bootcamp course, you'll learn key concepts and gain hands-on experience through weekly projects. Each chapter in this book is presented as a full week of topics, with Monday through ...
Python Projects for Beginners: A Ten-Week Bootcamp Approach to Python Programming
Immerse yourself in learning Python and introductory data analytics with this book's project-based approach. Through the structure of a ten-week coding bootcamp course, you'll learn key concepts and gain hands-on experience through weekly projects. Each chapter in this book is presented as a full week of topics, with Monday through Thursday covering specific concepts, leading up to Friday, when you are challenged to create a project using the skills learned throughout the week. Topics include Python basics and essential intermediate concepts such as list comprehension, generators and iterators, understanding algorithmic complexity, and data analysis with pandas. From beginning to end, this book builds up your abilities through exercises and challenges, culminating in your solid understanding of Python. Challenge yourself with the intensity of a coding bootcamp experience or learn at your own pace. With this hands-on learning approach, you will gain the skills you need to jumpstart a new career in programming or further your current one as a software developer. What You Will Learn Understand beginning and more advanced concepts of the Python language Be introduced to data analysis using pandas, the Python Data Analysis library Walk through the process of interviewing and answering technical questions Create real-world applications with the Python language Learn how to use Anaconda, Jupyter Notebooks, and the Python Shell Who This Book Is For Those trying to jumpstart a new career into programming, and those already in the software development industry and would like to learn Python programming.
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39.890000 USD

Python Projects for Beginners: A Ten-Week Bootcamp Approach to Python Programming

by Connor P. Milliken
Paperback / softback
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Discover the methodologies and best practices for getting started with Google Cloud Platform relational services - CloudSQL and CloudSpanner. The book begins with the basics of working with the Google Cloud Platform along with an introduction to the database technologies available for developers from Google Cloud. You'll then take an ...
Hands On Google Cloud SQL and Cloud Spanner: Deployment, Administration and Use Cases with Python
Discover the methodologies and best practices for getting started with Google Cloud Platform relational services - CloudSQL and CloudSpanner. The book begins with the basics of working with the Google Cloud Platform along with an introduction to the database technologies available for developers from Google Cloud. You'll then take an in-depth hands on journey into Google CloudSQL and CloudSpanner, including choosing the right platform for your application needs, planning, provisioning, designing and developing your application. Sample applications are given that use Python to connect to CloudSQL and CloudSpanner, along with helpful features provided by the engines. You''ll also implement practical best practices in the last chapter. Hands On Google Cloud SQL and Cloud Spanner is a great starting point to apply GCP data offerings in your technology stack and the code used allows you to try out the examples and extend them in interesting ways. What You'll Learn Get started with Big Data technologies on the Google Cloud Platform Review CloudSQL and Cloud Spanner from basics to administration Apply best practices and use Google's CloudSQL and CloudSpanner offering Work with code in Python notebooks and scripts Who This Book Is For Application architects, database architects, software developers, data engineers, cloud architects.
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39.890000 USD

Hands On Google Cloud SQL and Cloud Spanner: Deployment, Administration and Use Cases with Python

by Shakuntala Gupta Edward, Navin Sabharwal
Paperback / softback
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Cognitive Virtual Bots are taking the technology and user experience world by storm. This book provides clear guidance on how different cognitive platforms can be used to develop Cognitive Virtual Assistants that enable a conversation by using DialogFlow and advanced Natural Language Processing. You will start by understanding the technology ...
Developing Cognitive Bots Using the IBM Watson Engine: Practical, Hands-on Guide to Developing Complex Cognitive Bots Using IBM Watson Platform
Cognitive Virtual Bots are taking the technology and user experience world by storm. This book provides clear guidance on how different cognitive platforms can be used to develop Cognitive Virtual Assistants that enable a conversation by using DialogFlow and advanced Natural Language Processing. You will start by understanding the technology landscape and various use cases that Cognitive Virtual Assistants can be used in. Early chapters will take you through the basics of Cognitive Virtual Assistants, before moving onto advanced concepts and hands on examples of using IBM Watson Assistant and its advanced configurations with Watson Discovery Services, Watson Knowledge Studio and Spellchecker Service. You'll then examine integrations that enrich the Cognitive Virtual Assistant by providing data around weather, locations, stock markets. The book concludes by providing a glimpse of what to expect in the future for Cognitive Virtual Assistants. What You'll Learn Review the fundamentals of Cognitive Virtual Assistants. Develop a Cognitive Virtual Assistant from scratch using IBM Watson platform. Integrate and enrich your Virtual Agent with other services such as weather, location and stocks. Instantly deliver your bot on major messaging channels such as Skype, SMS, and Webchat Train your Cognitive Virtual Agent on specific use cases. Who This Book Is ForAI and machine learning engineers, cognitive solutions architects and developers would find the book extremely useful
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34.640000 USD

Developing Cognitive Bots Using the IBM Watson Engine: Practical, Hands-on Guide to Developing Complex Cognitive Bots Using IBM Watson Platform

by Pallavi Aggarwal, Neha Anand, Sudipta Barua, Navin Sabharwal
Paperback / softback
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Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python. You'll start by walking through the basics of fuzzy sets and relations, and ...
Deep Neuro-Fuzzy Systems with Python: With Case Studies and Applications from the Industry
Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python. You'll start by walking through the basics of fuzzy sets and relations, and how each member of the set has its own membership function values. You'll also look at different architectures and models that have been developed, and how rules and reasoning have been defined to make the architectures possible. The book then provides a closer look at neural networks and related architectures, focusing on the various issues neural networks may encounter during training, and how different optimization methods can help you resolve them. In the last section of the book you'll examine the integrations of fuzzy logics and neural networks, the adaptive neuro fuzzy Inference systems, and various approximations related to the same. You'll review different types of deep neuro fuzzy classifiers, fuzzy neurons, and the adaptive learning capability of the neural networks. The book concludes by reviewing advanced neuro fuzzy models and applications. What You'll Learn Understand fuzzy logic, membership functions, fuzzy relations, and fuzzy inference Review neural networks, back propagation, and optimization Work with different architectures such as Takagi-Sugeno model, Hybrid model, genetic algorithms, and approximations Apply Python implementations of deep neuro fuzzy system Who This book Is For Data scientists and software engineers with a basic understanding of Machine Learning who want to expand into the hybrid applications of deep learning and fuzzy logic.
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34.640000 USD

Deep Neuro-Fuzzy Systems with Python: With Case Studies and Applications from the Industry

by Yunis Ahmad Lone, Himanshu Singh
Paperback / softback
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Explore microservices using the Python-based Django framework and review the benefits and drawbacks of them. This book will examine what microservices look like, how they talk to each other, and how they are crafted using the Python programming language and the Django web framework. You'll start by understanding what the ...
Designing Microservices with Django: An Overview of Tools and Practices
Explore microservices using the Python-based Django framework and review the benefits and drawbacks of them. This book will examine what microservices look like, how they talk to each other, and how they are crafted using the Python programming language and the Django web framework. You'll start by understanding what the key differences are between microservices and monolithic architectures. The book then does a deep dive into how microservices are built and what common models have emerged in our industry. You'll also take an extensive look at communication and ownership patterns and examine methodologies to speed up your architecture evolution by writing less but more distributed code using the Python programming language and the Django web framework. By the end of the book, you'll have a solid understanding of microservices architectures. Armed with a comprehensive and solid toolset, you can begin working toward systems that are more scalable, resilient, and maintainable. What You'll Learn Understand the benefits and drawbacks of adopting microservices Design systems and architecture for resiliency and distributed ownership Work with tools for scaling distributed system both in technical and organizational dimensions Examine the essentials of the Django web framework
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46.47 USD

Designing Microservices with Django: An Overview of Tools and Practices

by Akos Hochrein
Paperback / softback
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Object Design Style Guide captures dozens of techniques for creating pro-quality OO code that can stand the test of time. Examples are in an instantly-familiar pseudocode, teaching techniques you can apply to any OO language, from C++ to PHP. The design rules for different types of objects Best practices for ...
Object Design Style Guide
Object Design Style Guide captures dozens of techniques for creating pro-quality OO code that can stand the test of time. Examples are in an instantly-familiar pseudocode, teaching techniques you can apply to any OO language, from C++ to PHP. The design rules for different types of objects Best practices for naming objects Testing an object's behavior instead of its implementation Exercises for each chapter to test your design skills
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41.990000 USD

Object Design Style Guide

by Matthias Noback
Paperback / softback
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Python is a remarkably powerful dynamic programming language used in a wide variety of situations such as Web, database access, desktop GUIs, game and software development, and network programming. Fans of Python use the phrase batteries included to describe the standard library, which covers everything from asynchronous processing to zip ...
Python: Visual QuickStart Guide
Python is a remarkably powerful dynamic programming language used in a wide variety of situations such as Web, database access, desktop GUIs, game and software development, and network programming. Fans of Python use the phrase batteries included to describe the standard library, which covers everything from asynchronous processing to zip files. The language itself is a flexible powerhouse that can handle practically any application domain. This task-based tutorial on Python is for those new to the language and walks you through the fundamentals. You'll learn about arithmetic, strings, and variables; writing programs; flow of control, functions; strings; data structures; input and output; and exception handling. At the end of the book, a special section walks you through a longer, realistic application, tying the concepts of the book together.
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62.09 USD

Python: Visual QuickStart Guide

by Toby Donaldson
Mixed media product
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Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you'll learn how to build features that use powerful ...
Practical Artificial Intelligence with Swift: From Fundamental Theory to Development of AI-Driven Apps
Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you'll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more. AI is increasingly essential for every developer-and you don't need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple's Python-powered Turi Create and Google's Swift for TensorFlow to train and build models. I: Fundamentals and Tools-Learn AI basics, our task-based approach, and discover how to build or find a dataset. II: Task Based AI-Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models. III: Beyond-Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch... if you want to
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62.990000 USD

Practical Artificial Intelligence with Swift: From Fundamental Theory to Development of AI-Driven Apps

by Tim Nugent, Paris Buttfield-Addison, Jonathon Manning, Mars Geldard
Paperback / softback
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Modernize and upgrade your enterprise ERP environment by learning to work with the stable and essential components of Odoo 12 from scratch Key Features Learn the fundamentals of Odoo, a comprehensive enterprise management platform, without writing a single line of code Create business operation strategies and analytics by using Odoo ...
Learn Odoo: A beginner's guide to designing, configuring, and customizing business applications with Odoo
Modernize and upgrade your enterprise ERP environment by learning to work with the stable and essential components of Odoo 12 from scratch Key Features Learn the fundamentals of Odoo, a comprehensive enterprise management platform, without writing a single line of code Create business operation strategies and analytics by using Odoo Build customized ERP and CRM solutions for your business Book DescriptionOdoo is management software that contains a set of open source enterprise management applications that help you modernize your business. Completely revised and updated, this comprehensive Odoo guide is a fourth edition of Working with Odoo. This book begins with an introduction to Odoo and helps you set up Odoo Online in your system. You'll learn how to start a new company database in Odoo and the basics of Odoo sales management. You will explore customer relationship management in Odoo and its importance in a modern business environment. Moving on, you'll learn how to install the purchasing application, set up suppliers, and begin purchasing and receiving products in Odoo. Next, you'll learn how to use the MRP module to create, process, and schedule the manufacturing and production order. Once you get to grips with the basic applications, you'll uncover how to customize Odoo to meet the specific needs of your business. You'll learn some advanced techniques for searching and finding information, and you'll be taken through business intelligence in Odoo. Towards the end of the book, you'll go in-depth into Odoo's architecture and learn to use Odoo's API to integrate with other applications. By the end of the book, you'll be ready to use Odoo to build enterprise applications and set up the functional requirements for your business. What you will learn Configure and customize a customer relationship management system Set up purchasing and receiving system functionality in your Odoo environment Understand manufacturing operations and processes with real-world examples Explore Odoo's financial accounting and reporting features Use Odoo's featured project management application to sort tasks Get to grips with the basics of Odoo administration and manage multi-company operations Who this book is forThis book is for any IT professionals, business managers, and operation managers who are looking to gain a functional understanding of Odoo or trying to implement Odoo in their organization to improve their business processes. No prior experience of Odoo is required.
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52.490000 USD

Learn Odoo: A beginner's guide to designing, configuring, and customizing business applications with Odoo

by Greg Moss
Paperback / softback
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Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks-one that ...
GANs in Action
Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks-one that generates content and the other that rejects samples that are of poor quality. GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you'll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you'll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks. Key Features * Understanding GANs and their potential * Hands-on code tutorials to build GAN models * Advanced GAN architectures and techniques like Cycle-Consistent Adversarial Networks * Handling the progressive growing of GANs * Practical applications of GANs Written for data scientists and data analysts with intermediate Python knowledge. Knowing the basics of deep learning will also be helpful. About the technology GANs have already achieved remarkable results that have been thought impossible for artificial systems, such as the ability to generate realistic faces, turn a scribble into a photograph-like image, are turn video footage of a horse into a running zebra. Most importantly, GANs learn quickly without the need for vast troves of painstakingly labeled training data. Jakub Langr graduated from Oxford University where he also taught at OU Computing Services. He has worked in data science since 2013, most recently as a data science Tech Lead at Filtered.com and as a data science consultant at Mudano. Jakub also designed and teaches Data Science courses at the University of Birmingham and is a fellow of the Royal Statistical Society. Vladimir Bok is a Senior Product Manager at Intent Media, a data science company for leading travel sites, where he helps oversee the company's Machine Learning research and infrastructure teams. Prior to that, he was a Program Manager at Microsoft. Vladimir graduated Cum Laude with a degree in Computer Science from Harvard University. He has worked as a software engineer at early stage FinTech companies, including one founded by PayPal co-founder Max Levchin, and as a Data Scientist at a Y Combinator startup.
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52.490000 USD

GANs in Action

by Vladimir Bok, Jakub Langr
Paperback / softback
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Statistics is the activity of inferring results about a population given a sample. Historically, statistics books assume an underlying distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot normally be sure of the underlying distribution. For that reason, this ...
Statistics is Easy!
Statistics is the activity of inferring results about a population given a sample. Historically, statistics books assume an underlying distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot normally be sure of the underlying distribution. For that reason, this book presents a distribution-independent approach to statistics based on a simple computational counting idea called resampling. This book explains the basic concepts of resampling, then system atically presents the standard statistical measures along with programs (in the language Python) to calculate them using resampling, and finally illustrates the use of the measures and programs in a case study. The text uses junior high school algebra and many examples to explain the concepts. Th e ideal reader has mastered at least elementary mathematics, likes to think procedurally, and is comfortable with computers.
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50.36 USD

Statistics is Easy!

by Manda Wilson, Dennis Shasha
Paperback / softback
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Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, ...
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow-author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
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111.56 USD

Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

by Aurelien Geron
Paperback / softback
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Explore modern game development and programming techniques to build games using Python and its popular libraries such as Pygame and PyOpenGL Key Features Learn game development and Python through a practical, example-driven approach Discover a variety of game development techniques to build games that gradually increase in complexity Leverage popular ...
Learning Python by Building Games: A beginner's guide to Python programming and game development
Explore modern game development and programming techniques to build games using Python and its popular libraries such as Pygame and PyOpenGL Key Features Learn game development and Python through a practical, example-driven approach Discover a variety of game development techniques to build games that gradually increase in complexity Leverage popular Python gaming libraries such as Pygame, PyOpenGL, Pymunk, and Pyglet Book DescriptionA fun and interactive way to get started with the Python language and its libraries is by getting hands-on with game development. Learning Python by Building Games brings you the best of both worlds. The book will first introduce you to Python fundamentals, which you will then use to develop a basic game. You'll gradually explore the different Python libraries best suited for game development such as Pygame, Pyglet, and PyOpenGL. From building game characters through to using 3D animation techniques, you'll discover how to create an aesthetic game environment. In addition to this, you'll focus on game physics to give your effects a realistic feel, complete with movements and collisions. The book will also cover how you can use particle systems to simulate phenomena such as an explosion or smoke. In later chapters, you will gain insights into object-oriented programming by modifying a snake game, along with exploring GUI programming to build a user interface with Python's turtle module. By the end of this book, you'll be well-versed with Python programming concepts and popular libraries, and have the confidence to build your own games What you will learn Explore core Python concepts by understanding Python libraries Build your first 2D game using Python scripting Understand concepts such as decorators and properties in the Python ecosystem Create animations and movements by building a Flappy Bird-like game Design game objects and characters using Pygame, PyOpenGL, and Pymunk Add intelligence to your gameplay by incorporating game artificial intelligence (AI) techniques using Python Who this book is forIf you are completely new to Python or game programming and want to develop your programming skills, then this book is for you. The book also acts as a refresher for those who already have experience of using Python and want to learn how to build exciting games.
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36.740000 USD

Learning Python by Building Games: A beginner's guide to Python programming and game development

by Sachin Kafle
Paperback / softback
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Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation ...
Beginning Anomaly Detection Using Python-Based Deep Learning: With Keras and PyTorch
Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation of what anomaly detection is, what it is used for, and its importance. After covering statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to deep learning with details on how to build and train a deep learning model in both Keras and PyTorch before shifting the focus to applications of the following deep learning models to anomaly detection: various types of Autoencoders, Restricted Boltzmann Machines, RNNs & LSTMs, and Temporal Convolutional Networks. The book explores unsupervised and semi-supervised anomaly detection along with the basics of time series-based anomaly detection. By the end of the book you will have a thorough understanding of the basic task of anomaly detection as well as an assortment of methods to approach anomaly detection, ranging from traditional methods to deep learning. Additionally, you are introduced to Scikit-Learn and are able to create deep learning models in Keras and PyTorch. What You Will Learn Understand what anomaly detection is and why it is important in today's world Become familiar with statistical and traditional machine learning approaches to anomaly detection using Scikit-Learn Know the basics of deep learning in Python using Keras and PyTorch Be aware of basic data science concepts for measuring a model's performance: understand what AUC is, what precision and recall mean, and more Apply deep learning to semi-supervised and unsupervised anomaly detection Who This Book Is For Data scientists and machine learning engineers interested in learning the basics of deep learning applications in anomaly detection
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39.890000 USD

Beginning Anomaly Detection Using Python-Based Deep Learning: With Keras and PyTorch

by Suman Kalyan Adari, Sridhar Alla
Paperback / softback
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Take the next steps toward mastering deep learning, the machine learning method that's transforming the world around us by the second. In this practical book, you'll get up to speed on key ideas using Facebook's open source PyTorch framework and gain the latest skills you need to create your very ...
Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications
Take the next steps toward mastering deep learning, the machine learning method that's transforming the world around us by the second. In this practical book, you'll get up to speed on key ideas using Facebook's open source PyTorch framework and gain the latest skills you need to create your very own neural networks. Ian Pointer shows you how to set up PyTorch on a cloud-based environment, then walks you through the creation of neural architectures that facilitate operations on images, sound, text, and more through deep dives into each element. He also covers the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production. Learn how to deploy deep learning models to production Explore PyTorch use cases from several leading companies Learn how to apply transfer learning to images Apply cutting-edge NLP techniques using a model trained on Wikipedia Use PyTorch's torchaudio library to classify audio data with a convolutional-based model Debug PyTorch models using TensorBoard and flame graphs Deploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud
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74.37 USD

Programming PyTorch for Deep Learning: Creating and Deploying Deep Learning Applications

by Ian Pointer
Paperback / softback
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Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can ...
Data Science at Scale with Python and Dask
Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the reader's analysis. Key Features Working with large structured datasets Writing DataFrames Cleaningand visualizing DataFrames Machine learning with Dask-ML Working with Bags and Arrays Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required. About the technology Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets. Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course.
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52.490000 USD

Data Science at Scale with Python and Dask

by Jesse C Daniel
Paperback / softback
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Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In Advanced Applied Deep Learning, you will study advanced topics on CNN and object detection using Keras and TensorFlow. Along ...
Advanced Applied Deep Learning: Convolutional Neural Networks and Object Detection
Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In Advanced Applied Deep Learning, you will study advanced topics on CNN and object detection using Keras and TensorFlow. Along the way, you will look at the fundamental operations in CNN, such as convolution and pooling, and then look at more advanced architectures such as inception networks, resnets, and many more. While the book discusses theoretical topics, you will discover how to work efficiently with Keras with many tricks and tips, including how to customize logging in Keras with custom callback classes, what is eager execution, and how to use it in your models. Finally, you will study how object detection works, and build a complete implementation of the YOLO (you only look once) algorithm in Keras and TensorFlow. By the end of the book you will have implemented various models in Keras and learned many advanced tricks that will bring your skills to the next level. What You Will Learn See how convolutional neural networks and object detection work Save weights and models on disk Pause training and restart it at a later stage Use hardware acceleration (GPUs) in your code Work with the Dataset TensorFlow abstraction and use pre-trained models and transfer learning Remove and add layers to pre-trained networks to adapt them to your specific project Apply pre-trained models such as Alexnet and VGG16 to new datasets Who This Book Is For Scientists and researchers with intermediate-to-advanced Python and machine learning know-how. Additionally, intermediate knowledge of Keras and TensorFlow is expected.
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34.640000 USD

Advanced Applied Deep Learning: Convolutional Neural Networks and Object Detection

by Umberto Michelucci
Paperback / softback
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Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration ...
Python for the Life Sciences: A Gentle Introduction to Python for Life Scientists
Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research. Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population. Best of all, Python for the Life Sciences shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you. What You'll Learn Write Python scripts to automate your lab calculations Search for important motifs in genome sequences Use object-oriented programming with Python Study mining interaction network data for patterns Review dynamic modeling of biochemical switches Who This Book Is For Life scientists with little or no programming experience, including undergraduate and graduate students, postdoctoral researchers in academia and industry, medical professionals, and teachers/lecturers. A comprehensive introduction to using Python for computational biology... A lovely book with humor and perspective -- John Novembre, Associate Professor of Human Genetics, University of Chicago and MacArthur Fellow Fun, entertaining, witty and darn useful. A magical portal to the big data revolution -- Sandro Santagata, Assistant Professor in Pathology, Harvard Medical School Alex and Gordon's enthusiasm for Python is contagious -- Glenys Thomson Professor of Integrative Biology, University of California, Berkeley
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39.890000 USD

Python for the Life Sciences: A Gentle Introduction to Python for Life Scientists

by Gordon Webster, Alexander Lancaster
Paperback / softback
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Develop a greater intuition for the proper use of cryptography. This book teaches the basics of writing cryptographic algorithms in Python, demystifies cryptographic internals, and demonstrates common ways cryptography is used incorrectly. Cryptography is the lifeblood of the digital world's security infrastructure. From governments around the world to the average ...
Practical Cryptography in Python: Learning Correct Cryptography by Example
Develop a greater intuition for the proper use of cryptography. This book teaches the basics of writing cryptographic algorithms in Python, demystifies cryptographic internals, and demonstrates common ways cryptography is used incorrectly. Cryptography is the lifeblood of the digital world's security infrastructure. From governments around the world to the average consumer, most communications are protected in some form or another by cryptography. These days, even Google searches are encrypted. Despite its ubiquity, cryptography is easy to misconfigure, misuse, and misunderstand. Developers building cryptographic operations into their applications are not typically experts in the subject, and may not fully grasp the implication of different algorithms, modes, and other parameters. The concepts in this book are largely taught by example, including incorrect uses of cryptography and how bad cryptography can be broken. By digging into the guts of cryptography, you can experience what works, what doesn't, and why. What You'll Learn Understand where cryptography is used, why, and how it gets misused Know what secure hashing is used for and its basic properties Get up to speed on algorithms and modes for block ciphers such as AES, and see how bad configurations break Use message integrity and/or digital signatures to protect messages Utilize modern symmetric ciphers such as AES-GCM and CHACHA Practice the basics of public key cryptography, including ECDSA signatures Discover how RSA encryption can be broken if insecure padding is used Employ TLS connections for secure communications Find out how certificates work and modern improvements such as certificate pinning and certificate transparency (CT) logs Who This Book Is For IT administrators and software developers familiar with Python. Although readers may have some knowledge of cryptography, the book assumes that the reader is starting from scratch.
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39.890000 USD

Practical Cryptography in Python: Learning Correct Cryptography by Example

by Christopher K. Monson, Seth James Nielson
Paperback / softback
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Are you using SAP ERP and eager to unlock the enormous value of its data? With this practical guide, SAP veterans Greg Foss and Paul Modderman show you how to use several data analysis tools to solve interesting problems with your SAP data. Throughout the book, you'll follow a fictional ...
Practical Data Science with SAP: Machine Learning Techniques for Enterprise Data
Are you using SAP ERP and eager to unlock the enormous value of its data? With this practical guide, SAP veterans Greg Foss and Paul Modderman show you how to use several data analysis tools to solve interesting problems with your SAP data. Throughout the book, you'll follow a fictional company as it tackles real scenarios. Using actual data to create example code and visualizations, SAP business analysts will learn practical methods for gaining deeper insights into their business's data. Data engineers and data scientists will explore ways to add SAP data to their analysis processes. Through grounded explanations of both SAP processes and data science tools, you'll discover powerful methods for discovering data truths. Use data to tell revealing stories about your customers Model purchase requisition data using exploratory data analysis Create an anomaly detection system for SAP sales orders Use R and Python to make predictions on sales data Cluster and segment your customers based on their buying habits Use association rule learning to discover customer buying patterns Apply NLP to uncover the most highly actionable customer complaints
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104.13 USD

Practical Data Science with SAP: Machine Learning Techniques for Enterprise Data

by Paul Modderman, Greg Foss
Paperback / softback
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Deep Learning with Pytorch
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52.490000 USD

Deep Learning with Pytorch

by Luca Antiga, Eli Stevens
Paperback / softback
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