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How can you use data in a way that protects individual privacy, but still ensures that data analytics will be useful and meaningful? With this practical book, data architects and engineers will learn how to implement and deploy anonymization solutions within a data collection pipeline. You'll establish and integrate secure, ...
Building an Anonymization Pipeline: Creating Safe Data
How can you use data in a way that protects individual privacy, but still ensures that data analytics will be useful and meaningful? With this practical book, data architects and engineers will learn how to implement and deploy anonymization solutions within a data collection pipeline. You'll establish and integrate secure, repeatable anonymization processes into your data flows and analytics in a sustainable manner. Luk Arbuckle and Khaled El Emam from Privacy Analytics explore end-to-end solutions for anonymizing data, based on data collection models and use cases enabled by real business needs. These examples come from some of the most demanding data environments, using approaches that have stood the test of time.
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52.490000 USD

Building an Anonymization Pipeline: Creating Safe Data

by Khaled El Emam, Luk Arbuckle
Paperback / softback
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Why does one smoker die of lung cancer but another live to 100? The answer is 'The Hidden Half' - those random, unknowable variables that mess up our attempts to comprehend the world. We humans are very clever creatures - but we're idiots about how clever we really are. In ...
The Hidden Half: How the World Conceals its Secrets
Why does one smoker die of lung cancer but another live to 100? The answer is 'The Hidden Half' - those random, unknowable variables that mess up our attempts to comprehend the world. We humans are very clever creatures - but we're idiots about how clever we really are. In this entertaining and ingenious book, Blastland reveals how in our quest to make the world more understandable, we lose sight of how unexplainable it often is. The result - from GDP figures to medicine - is that experts know a lot less than they think. Filled with compelling stories from economics, genetics, business, and science, The Hidden Half is a warning that an explanation which works in one arena may not work in another. Entertaining and provocative, it will change how you view the world.
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18.57 USD

The Hidden Half: How the World Conceals its Secrets

by Michael Blastland
Paperback / softback
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Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the tools, ...
Building Machine Learning Powered Applications: Going from Idea to Product
Learn the skills necessary to design, build, and deploy applications powered by machine learning. Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the tools, best practices, and challenges involved in building a real-world ML application step-by-step. Author Emmanuel Ameisen, who worked as a data scientist at Zipcar and led Insight Data Science's AI program, demonstrates key ML concepts with code snippets, illustrations, and screenshots from the book's example application. The first part of this guide shows you how to plan and measure success for an ML application. Part II shows you how to build a working ML model, and Part III explains how to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Determine your product goal and set up a machine learning problem Build your first end-to-end pipeline quickly and acquire an initial dataset Train and evaluate your ML model and address performance bottlenecks Deploy and monitor models in a production environment
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89.25 USD

Building Machine Learning Powered Applications: Going from Idea to Product

by Emmanuel Ameisen
Paperback / softback
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Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size--small enough to work on the digital signal processor in an Android phone. With this practical book, you'll learn about TensorFlow Lite for Microcontrollers, a miniscule ...
Tinyml: Machine Learning with Tensorflow on Arduino and Ultra-Low Power Micro-Controllers
Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size--small enough to work on the digital signal processor in an Android phone. With this practical book, you'll learn about TensorFlow Lite for Microcontrollers, a miniscule machine learning library that allows you to run machine learning algorithms on tiny hardware. Authors Pete Warden and Daniel Situnayake explain how you can train models that are small enough to fit into any environment, including small embedded devices that can run for a year or more on a single coin cell battery. Ideal for software and hardware developers who want to build embedded devices using machine learning, this guide shows you how to create a TinyML project step-by-step. No machine learning or microcontroller experience is necessary. Learn practical machine learning applications on embedded devices, including simple uses such as speech recognition and gesture detection Train models such as speech, accelerometer, and image recognition, you can deploy on Arduino and other embedded platforms Understand how to work with Arduino and ultralow-power microcontrollers Use techniques for optimizing latency, energy usage, and model and binary size
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74.37 USD

Tinyml: Machine Learning with Tensorflow on Arduino and Ultra-Low Power Micro-Controllers

by Daniel Situnayake, Pete Warden
Paperback / softback
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In this multidisciplinary book, experts from around the globe examine how data-driven political campaigning works, what challenges it poses for personal privacy and democracy, and how emerging practices should be regulated. The rise of big data analytics in the political process has triggered official investigations in many countries around the ...
Big Data, Political Campaigning and the Law: Democracy and Privacy in the Age of Micro-Targeting
In this multidisciplinary book, experts from around the globe examine how data-driven political campaigning works, what challenges it poses for personal privacy and democracy, and how emerging practices should be regulated. The rise of big data analytics in the political process has triggered official investigations in many countries around the world, and become the subject of broad and intense debate. Political parties increasingly rely on data analytics to profile the electorate and to target specific voter groups with individualised messages based on their demographic attributes. Political micro-targeting has become a major factor in modern campaigning, because of its potential to influence opinions, to mobilise supporters and to get out votes. The book explores the legal, philosophical and political dimensions of big data analytics in the electoral process. It demonstrates that the unregulated use of big personal data for political purposes not only infringes voters' privacy rights, but also has the potential to jeopardise the future of the democratic process, and proposes reforms to address the key regulatory and ethical questions arising from the mining, use and storage of massive amounts of voter data. Providing an interdisciplinary assessment of the use and regulation of big data in the political process, this book will appeal to scholars from law, political science, political philosophy, and media studies, policy makers and anyone who cares about democracy in the age of data-driven political campaigning.
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213.86 USD

Big Data, Political Campaigning and the Law: Democracy and Privacy in the Age of Micro-Targeting

Hardback
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This volume, Intelligent Systems: Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics, helps to fill the gap between data analytics, image processing, and soft computing practices. Soft computing methods are used to focus on data analytics and image processing approaches to develop good intelligent systems. To this ...
Intelligent Systems: Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics
This volume, Intelligent Systems: Advances in Biometric Systems, Soft Computing, Image Processing, and Data Analytics, helps to fill the gap between data analytics, image processing, and soft computing practices. Soft computing methods are used to focus on data analytics and image processing approaches to develop good intelligent systems. To this end, readers will find quality research that presents the current trends, advanced techniques, and hybridized techniques relating to data analytics and intelligence systems. The book also features case studies related to medical diagnosis with the use of image processing or soft computing algorithms in a particular models. Topics include some of the most important challenges and discoveries in intelligent systems today, such as computer vision concepts and image identification, data analysis and computational paradigms, deep learning techniques, face and speaker recognition systems, and more.
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178.450000 USD
Hardback
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Understand the concepts and methodologies to manage and deliver top-notch Data Science solutions for your organization. Key Features *Learn to design, implement and maintain distributed data architectures with DataOps * Follow principles for building a better innovation process for your organization * Explore various challenges, possibilities, and limitations in Data ...
Managing Data Science: Effective strategies to manage data science projects efficiently and build a sustainable team
Understand the concepts and methodologies to manage and deliver top-notch Data Science solutions for your organization. Key Features *Learn to design, implement and maintain distributed data architectures with DataOps * Follow principles for building a better innovation process for your organization * Explore various challenges, possibilities, and limitations in Data Science Book Description Data Science and Machine Learning can transform any organization and open new opportunities. Any Data Science project is a unique mix of research, software engineering, and business expertise. A substantial managerial effort is needed to guide the solution from prototype development to production. Traditional approaches often fail as they have different conditions and requirements in mind. This book presents a proven approach to Data Science project management, with tips and best practices to guide you along the way. With the help of this book, you will understand the practical applications of data science and AI to incorporate them into your solutions. You will go through the Data Science project life-cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a balanced skillful team, and this book will present helpful advice for hiring and growing a skillful data science team for your organization. The book also shows you how you can efficiently manage and improve your Data Science projects through the use of DevOps. By the end of the book, the readers will have the practical knowledge to tackle various challenges they deal on a daily basis and will have an understanding of various data science solutions. What you will learn *Understand the underlying problems of building a strong Data Science pipeline * Learn about the different tools to build and deploy data science solution * Hire, grow, and sustain an efficient Data Science team * Manage data science projects through all stages from prototype to production * Learn how to use DevOps for improving Data Science projects * Master the techniques for testing models in all the stages Who This Book Is For The book is intended to Data Scientists, Analysts, as well as program managers who want to bring more productivity to their organization and improve their business by incorporating data science workflows efficiently. Some understanding of the basic data science concepts will be useful.
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31.490000 USD

Managing Data Science: Effective strategies to manage data science projects efficiently and build a sustainable team

by Kirill Dubovikov
Paperback / softback
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Control Systems Design of Bio-Robotics and Bio-Mechatronics with Advanced Applications delivers essential and advanced bioengineering information on the application of control and robotics technologies in the life sciences. Judging by what we have witnessed so far, this exciting field of control systems and robotics in bioengineering is likely to produce ...
Control Systems Design of Bio-Robotics and Bio-mechatronics with Advanced Applications
Control Systems Design of Bio-Robotics and Bio-Mechatronics with Advanced Applications delivers essential and advanced bioengineering information on the application of control and robotics technologies in the life sciences. Judging by what we have witnessed so far, this exciting field of control systems and robotics in bioengineering is likely to produce revolutionary breakthroughs over the next decade. While this book is intended for senior undergraduate or graduate students in both control engineering and biomedical engineering programs, it will also appeal to medical researchers and practitioners who want to enhance their quantitative understanding of physiological processes.
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157.500000 USD

Control Systems Design of Bio-Robotics and Bio-mechatronics with Advanced Applications

Paperback / softback
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Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and ...
Practical Time Series Analysis: Prediction with Statistics and Machine Learning
Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You'll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
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73.490000 USD

Practical Time Series Analysis: Prediction with Statistics and Machine Learning

by Aileen Nielsen
Paperback / softback
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This book constitutes revised and selected papers from the 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019, held in Ekaterinburg, Russia, in July 2019. The 40 full papers and 4 short papers presented in this volume were carefully reviewed and selected from a total of 170 ...
Mathematical Optimization Theory and Operations Research: 18th International Conference, MOTOR 2019, Ekaterinburg, Russia, July 8 - 12, 2019, Revised Selected Papers
This book constitutes revised and selected papers from the 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019, held in Ekaterinburg, Russia, in July 2019. The 40 full papers and 4 short papers presented in this volume were carefully reviewed and selected from a total of 170 submissions. The papers in the volume are organised according to the following topical headings: combinatorial optimization; game theory and mathematical economics; data mining and computational geometry; integer programming; mathematical programming; operations research; optimal control and applications.
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115.490000 USD

Mathematical Optimization Theory and Operations Research: 18th International Conference, MOTOR 2019, Ekaterinburg, Russia, July 8 - 12, 2019, Revised Selected Papers

Paperback / softback
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Perform advanced data manipulation tasks using pandas and become an expert data analyst. Key Features Manipulate and analyze your data expertly using the power of pandas Work with missing data and time series data and become a true pandas expert Includes expert tips and techniques on making your data analysis ...
Mastering pandas: A complete guide to pandas, from installation to advanced data analysis techniques, 2nd Edition
Perform advanced data manipulation tasks using pandas and become an expert data analyst. Key Features Manipulate and analyze your data expertly using the power of pandas Work with missing data and time series data and become a true pandas expert Includes expert tips and techniques on making your data analysis tasks easier Book Descriptionpandas is a popular Python library used by data scientists and analysts worldwide to manipulate and analyze their data. This book presents useful data manipulation techniques in pandas to perform complex data analysis in various domains. An update to our highly successful previous edition with new features, examples, updated code, and more, this book is an in-depth guide to get the most out of pandas for data analysis. Designed for both intermediate users as well as seasoned practitioners, you will learn advanced data manipulation techniques, such as multi-indexing, modifying data structures, and sampling your data, which allow for powerful analysis and help you gain accurate insights from it. With the help of this book, you will apply pandas to different domains, such as Bayesian statistics, predictive analytics, and time series analysis using an example-based approach. And not just that; you will also learn how to prepare powerful, interactive business reports in pandas using the Jupyter notebook. By the end of this book, you will learn how to perform efficient data analysis using pandas on complex data, and become an expert data analyst or data scientist in the process. What you will learn Speed up your data analysis by importing data into pandas Keep relevant data points by selecting subsets of your data Create a high-quality dataset by cleaning data and fixing missing values Compute actionable analytics with grouping and aggregation in pandas Master time series data analysis in pandas Make powerful reports in pandas using Jupyter notebooks Who this book is forThis book is for data scientists, analysts and Python developers who wish to explore advanced data analysis and scientific computing techniques using pandas. Some fundamental understanding of Python programming and familiarity with the basic data analysis concepts is all you need to get started with this book.
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47.240000 USD

Mastering pandas: A complete guide to pandas, from installation to advanced data analysis techniques, 2nd Edition

by Ashish Kumar
Paperback / softback
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Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applications Key Features Discover the new features introduced in Elasticsearch 7 Explore techniques for distributed search, indexing, and clustering Gain hands-on knowledge of implementing Elasticsearch for your enterprise Book DescriptionElasticsearch is one of the most ...
Elasticsearch 7 Quick Start Guide: Get up and running with the distributed search and analytics capabilities of Elasticsearch
Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applications Key Features Discover the new features introduced in Elasticsearch 7 Explore techniques for distributed search, indexing, and clustering Gain hands-on knowledge of implementing Elasticsearch for your enterprise Book DescriptionElasticsearch is one of the most popular tools for distributed search and analytics. This Elasticsearch book highlights the latest features of Elasticsearch 7 and helps you understand how you can use them to build your own search applications with ease. Starting with an introduction to the Elastic Stack, this book will help you quickly get up to speed with using Elasticsearch. You'll learn how to install, configure, manage, secure, and deploy Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. As you progress, you'll also understand how to troubleshoot any issues that you may encounter along the way. Finally, the book will help you explore the inner workings of Elasticsearch and gain insights into queries, analyzers, mappings, and aggregations as you learn to work with search results. By the end of this book, you'll have a basic understanding of how to build and deploy effective search and analytics solutions using Elasticsearch. What you will learn Install Elasticsearch and use it to safely store data and retrieve it when needed Work with a variety of analyzers and filters Discover techniques to improve search results in Elasticsearch Understand how to perform metric and bucket aggregations Implement best practices for moving clusters and applications to production Explore various techniques to secure your Elasticsearch clusters Who this book is forThis book is for software developers, engineers, data architects, system administrators, and anyone who wants to get up and running with Elasticsearch 7. No prior experience with Elasticsearch is required.
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31.490000 USD

Elasticsearch 7 Quick Start Guide: Get up and running with the distributed search and analytics capabilities of Elasticsearch

by Douglas Miller, Anurag Srivastava
Paperback / softback
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Applied Analysis of Composite Media: Analytical and Computational Approaches presents formulas and techniques that can used to study 2D and 3D problems in composites and random porous media. The main strength of this book is its broad range of applications that illustrate how these techniques can be applied to investigate ...
Applied Analysis of Composite Media: Analytical and Computational Results for Materials Scientists and Engineers
Applied Analysis of Composite Media: Analytical and Computational Approaches presents formulas and techniques that can used to study 2D and 3D problems in composites and random porous media. The main strength of this book is its broad range of applications that illustrate how these techniques can be applied to investigate elasticity, viscous flow and bacterial motion in composite materials. In addition to paying attention to constructive computations, the authors have also included information on codes via a designated webpage. This book will be extremely useful for postgraduate students, academic researchers, mathematicians and industry professionals who are working in structured media.
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236.250000 USD

Applied Analysis of Composite Media: Analytical and Computational Results for Materials Scientists and Engineers

by Wojciech Nawalaniec, Vladimir Mityushev, Simon Gluzman, Piotr Drygas
Paperback / softback
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Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Key Features Learn, develop, and deploy advanced reinforcement learning algorithms to solve a variety of tasks Understand and develop model-free and model-based algorithms for building self-learning agents Work with advanced Reinforcement Learning concepts and algorithms such ...
Reinforcement Learning Algorithms with Python: Learn, understand, and develop smart algorithms for addressing AI challenges
Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Key Features Learn, develop, and deploy advanced reinforcement learning algorithms to solve a variety of tasks Understand and develop model-free and model-based algorithms for building self-learning agents Work with advanced Reinforcement Learning concepts and algorithms such as imitation learning and evolution strategies Book DescriptionReinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. This book will help you master RL algorithms and understand their implementation as you build self-learning agents. Starting with an introduction to the tools, libraries, and setup needed to work in the RL environment, this book covers the building blocks of RL and delves into value-based methods, such as the application of Q-learning and SARSA algorithms. You'll learn how to use a combination of Q-learning and neural networks to solve complex problems. Furthermore, you'll study the policy gradient methods, TRPO, and PPO, to improve performance and stability, before moving on to the DDPG and TD3 deterministic algorithms. This book also covers how imitation learning techniques work and how Dagger can teach an agent to drive. You'll discover evolutionary strategies and black-box optimization techniques, and see how they can improve RL algorithms. Finally, you'll get to grips with exploration approaches, such as UCB and UCB1, and develop a meta-algorithm called ESBAS. By the end of the book, you'll have worked with key RL algorithms to overcome challenges in real-world applications, and be part of the RL research community. What you will learn Develop an agent to play CartPole using the OpenAI Gym interface Discover the model-based reinforcement learning paradigm Solve the Frozen Lake problem with dynamic programming Explore Q-learning and SARSA with a view to playing a taxi game Apply Deep Q-Networks (DQNs) to Atari games using Gym Study policy gradient algorithms, including Actor-Critic and REINFORCE Understand and apply PPO and TRPO in continuous locomotion environments Get to grips with evolution strategies for solving the lunar lander problem Who this book is forIf you are an AI researcher, deep learning user, or anyone who wants to learn reinforcement learning from scratch, this book is for you. You'll also find this reinforcement learning book useful if you want to learn about the advancements in the field. Working knowledge of Python is necessary.
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36.740000 USD

Reinforcement Learning Algorithms with Python: Learn, understand, and develop smart algorithms for addressing AI challenges

by Andrea Lonza
Paperback / softback
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If you're like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will ...
Mastering Spark with R: The Complete Guide to Large-Scale Analysis and Modeling
If you're like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions
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74.37 USD

Mastering Spark with R: The Complete Guide to Large-Scale Analysis and Modeling

by Edgar Ruiz, Kevin Kuo, Javier Luraschi
Paperback / softback
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This open access book presents nine outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di ...
Special Topics in Information Technology
This open access book presents nine outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Controls, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the nine best theses defended in 2018-19 and selected for the IT PhD Award. Each of the nine authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.
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26.240000 USD

Special Topics in Information Technology

Paperback / softback
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Numerical Modelling of Bulk Superconductor Magnetisation
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199.500000 USD

Numerical Modelling of Bulk Superconductor Magnetisation

by Hiroyuki Fujishiro, Dr Mark Ainslie
Hardback
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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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Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially ...
Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers
Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes. Predicting health outcomes using data modeling approaches is an emerging field that can reveal important insights into disproportionate spending patterns. This book presents data driven methods, especially machine learning, for understanding and approaching the high utilizers problem, using the example of a large public insurance program. It describes important goals for data driven approaches from different aspects of the high utilizer problem, and identifies challenges uniquely posed by this problem. Key Features: Introduces basic elements of health care data, especially for administrative claims data, including disease code, procedure codes, and drug codes Provides tailored supervised and unsupervised machine learning approaches for understanding and predicting the high utilizers Presents descriptive data driven methods for the high utilizer population Identifies a best-fitting linear and tree-based regression model to account for patients' acute and chronic condition loads and demographic characteristics
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251.06 USD

Data Driven Approaches for Healthcare: Machine learning for Identifying High Utilizers

by Sanjay Ranka, Elizabeth Shenkman, Chris Delcher, Chengliang Yang
Hardback
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This invaluable addition to any data scientist's library shows you how to apply the R programming language and useful statistical techniques to everyday business situations as well as how to effectively present results to audiences of all levels. To answer the ever-increasing demand for machine learning and analysis, this new ...
Practical Data Science with R
This invaluable addition to any data scientist's library shows you how to apply the R programming language and useful statistical techniques to everyday business situations as well as how to effectively present results to audiences of all levels. To answer the ever-increasing demand for machine learning and analysis, this new edition boasts additional R tools, modeling techniques, and more. Practical Data Science with R, Second Edition takes a practice oriented approach to explaining basic principles in the ever-expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. Key features * Data science and statistical analysis for the business professional * Numerous instantly familiar real-world use cases * Keys to effective data presentations * Modeling and analysis techniques like boosting, regularized regression, and quadratic discriminant analysis Audience While some familiarity with basic statistics and R is assumed, this book is accessible to readers with or without a background in data science. About the technology Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day Nina Zumel and John Mount are co-founders of Win-Vector LLC, a San Francisco-based data science consulting firm. Both hold PhDs from Carnegie Mellon and blog on statistics, probability, and computer science at win-vector.com.
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70.65 USD

Practical Data Science with R

by John Mount, Nina Zumel
Paperback / softback
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Understand how blockchain works and explore a variety of strategies to implement it in your organization effectively Key Features Become familiar with business challenges faced by companies when using blockchain Discover how companies implement blockchain to monetize and secure their data Study real-world examples to understand blockchain and its use ...
Blockchain for Decision Makers: A systematic guide to using blockchain for improving your business
Understand how blockchain works and explore a variety of strategies to implement it in your organization effectively Key Features Become familiar with business challenges faced by companies when using blockchain Discover how companies implement blockchain to monetize and secure their data Study real-world examples to understand blockchain and its use in organizations Book DescriptionIn addition to cryptocurrencies, blockchain-based apps are being developed in different industries such as banking, supply chain, and healthcare to achieve digital transformation and enhance user experience. Blockchain is not only about Bitcoin or cryptocurrencies, but also about different technologies such as peer-to-peer networks, consensus mechanisms, and cryptography. These technologies together help sustain trustless environments in which digital value can be transferred between individuals without intermediaries. This book will help you understand the basics of blockchain such as consensus protocols, decentralized applications, and tokenization. You'll focus on how blockchain is used today in different industries and the technological challenges faced while implementing a blockchain strategy. The book also enables you, as a decision maker, to understand blockchain from a technical perspective and evaluate its applicability in your business. Finally, you'll get to grips with blockchain frameworks such as Hyperledger and Quorum and their usability. By the end of this book, you'll have learned about the current use cases of blockchain and be able to implement a blockchain strategy on your own. What you will learn Become well-versed with how blockchain works Understand the difference between blockchain and Bitcoin Learn how blockchain is being used in different industry verticals such as finance and retail Delve into the technological and organizational challenges of implementing blockchain Explore the possibilities that blockchain can unlock for decision makers Choose a blockchain framework best suited for your projects from options such as Ethereum and Hyperledger Fabric Who this book is forThis book is for CXOs, business professionals, organization leaders, decision makers, technology enthusiasts, and managers who wish to understand how blockchain is implemented in different organizations, its impact, and how it can be customized according to business needs. Prior experience with blockchain is not required.
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36.740000 USD

Blockchain for Decision Makers: A systematic guide to using blockchain for improving your business

by Romain Tormen
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This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the ...
Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 2
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
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230.990000 USD

Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019, Volume 2

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With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You'll start with deep learning basics and move quickly to the ...
Deep Learning from Scratch: Building with Python from First Principles
With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You'll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You'll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you'll be set up for success on all future deep learning projects. This book provides: Extremely clear and thorough mental models-accompanied by working code examples and mathematical explanations-for understanding neural networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working implementations and clear-cut explanations of convolutional and recurrent neural networks Implementation of these neural network concepts using the popular PyTorch framework
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62.990000 USD

Deep Learning from Scratch: Building with Python from First Principles

by Seth Weidman
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A comprehensive guide to developing neural network-based solutions using TensorFlow 2.0 Key Features Understand the basics of machine learning and discover the power of neural networks and deep learning Explore the structure of the TensorFlow framework and understand how to transition to TF 2.0 Solve any deep learning problem by ...
Hands-On Neural Networks with TensorFlow 2.0: Understand TensorFlow, from static graph to eager execution, and design neural networks
A comprehensive guide to developing neural network-based solutions using TensorFlow 2.0 Key Features Understand the basics of machine learning and discover the power of neural networks and deep learning Explore the structure of the TensorFlow framework and understand how to transition to TF 2.0 Solve any deep learning problem by developing neural network-based solutions using TF 2.0 Book DescriptionTensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book covers machine learning with a focus on developing neural network-based solutions. You'll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you'll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub. By the end of this TensorFlow book, you'll be ready to solve any machine learning problem by developing solutions using TF 2.0 and putting them into production. What you will learn Grasp machine learning and neural network techniques to solve challenging tasks Apply the new features of TF 2.0 to speed up development Use TensorFlow Datasets (tfds) and the tf.data API to build high-efficiency data input pipelines Perform transfer learning and fine-tuning with TensorFlow Hub Define and train networks to solve object detection and semantic segmentation problems Train Generative Adversarial Networks (GANs) to generate images and data distributions Use the SavedModel file format to put a model, or a generic computational graph, into production Who this book is forIf you're a developer who wants to get started with machine learning and TensorFlow, or a data scientist interested in developing neural network solutions in TF 2.0, this book is for you. Experienced machine learning engineers who want to master the new features of the TensorFlow framework will also find this book useful. Basic knowledge of calculus and a strong understanding of Python programming will help you grasp the topics covered in this book.
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41.990000 USD

Hands-On Neural Networks with TensorFlow 2.0: Understand TensorFlow, from static graph to eager execution, and design neural networks

by Paolo Galeone
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This book constitutes the revised papers of the 45th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2019, held in Vall de Nuria, Spain, in June 2019. The 29 full papers presented in this volume were carefully reviewed and selected from 87 submissions. They cover a wide range of ...
Graph-Theoretic Concepts in Computer Science: 45th International Workshop, WG 2019, Vall de Nuria, Spain, June 19-21, 2019, Revised Papers
This book constitutes the revised papers of the 45th International Workshop on Graph-Theoretic Concepts in Computer Science, WG 2019, held in Vall de Nuria, Spain, in June 2019. The 29 full papers presented in this volume were carefully reviewed and selected from 87 submissions. They cover a wide range of areas, aiming at connecting theory and applications by demonstrating how graph-theoretic concepts can be applied in various areas of computer science. Another focus is on presenting recent results and on identifying and exploring promising directions of future research.
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83.990000 USD

Graph-Theoretic Concepts in Computer Science: 45th International Workshop, WG 2019, Vall de Nuria, Spain, June 19-21, 2019, Revised Papers

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With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal ...
Machine Learning Pocket Reference: Working with Structured Data in Python
With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
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26.240000 USD

Machine Learning Pocket Reference: Working with Structured Data in Python

by Matt Harrison
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This book constitutes the refereed proceedings of the 12th International Conference on Combinatorics on Words, WORDS 2019, held in Loughborough, UK, in September 2019. The 21 revised full papers presented in this book together with 5 invited talks were carefully reviewed and selected from 34 submissions. WORDS is the main ...
Combinatorics on Words: 12th International Conference, WORDS 2019, Loughborough, UK, September 9-13, 2019, Proceedings
This book constitutes the refereed proceedings of the 12th International Conference on Combinatorics on Words, WORDS 2019, held in Loughborough, UK, in September 2019. The 21 revised full papers presented in this book together with 5 invited talks were carefully reviewed and selected from 34 submissions. WORDS is the main conference series devoted to the mathematical theory of words. In particular, the combinatorial, algebraic and algorithmic aspects of words are emphasized. Motivations may also come from other domains such as theoretical computer science, bioinformatics, digital geometry, symbolic dynamics, numeration systems, text processing, number theory, etc.
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83.990000 USD

Combinatorics on Words: 12th International Conference, WORDS 2019, Loughborough, UK, September 9-13, 2019, Proceedings

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This volume constitutes the proceedings of the 13th International Conference on Algorithmic Aspects in Information and Management, AAIM 2019, held in Bejing, China in August 2019. The 31 full papers presented were carefully reviewed and selected. The papers deal with most aspects of theoretical computer science and their applications. Special ...
Algorithmic Aspects in Information and Management: 13th International Conference, AAIM 2019, Beijing, China, August 6-8, 2019, Proceedings
This volume constitutes the proceedings of the 13th International Conference on Algorithmic Aspects in Information and Management, AAIM 2019, held in Bejing, China in August 2019. The 31 full papers presented were carefully reviewed and selected. The papers deal with most aspects of theoretical computer science and their applications. Special considerations are given to algorithmic research that is motivated by real-world applications.
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83.990000 USD

Algorithmic Aspects in Information and Management: 13th International Conference, AAIM 2019, Beijing, China, August 6-8, 2019, Proceedings

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This book constitutes the proceedings of the 17th International Conference on Business Process Management, BPM 2019, held in Vienna, Austria, in September 2019. The 23 full and 4 tutorial short papers included in this volume were carefully reviewed and selected from 115 submissions. The papers were organized in topical sections ...
Business Process Management: 17th International Conference, BPM 2019, Vienna, Austria, September 1-6, 2019, Proceedings
This book constitutes the proceedings of the 17th International Conference on Business Process Management, BPM 2019, held in Vienna, Austria, in September 2019. The 23 full and 4 tutorial short papers included in this volume were carefully reviewed and selected from 115 submissions. The papers were organized in topical sections named: foundations; engineering; and management.
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94.490000 USD

Business Process Management: 17th International Conference, BPM 2019, Vienna, Austria, September 1-6, 2019, Proceedings

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