Mac eBooks
Foundations of Machine Learning, 2nd Edition
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and ...
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and ...
Machine Learning Yearning
AI is transforming numerous industries. Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects. This book is focused not on teaching you ML algorithms, but on how to make ML algorithms work. After reading Machine Learning Yearning, you will be able to: Prioritize the most promising directions for an AI project; Diagnose errors in a machine learning system; Build ML in complex settings, such as mismatched training/ test sets; Set up an ML project to compare to and/or surpass human - level performance; Know when and how to apply end-to-end learning, transfer learning, and multi-task learning. ...
AI is transforming numerous industries. Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects. This book is focused not on teaching you ML algorithms, but on how to make ML algorithms work. After reading Machine Learning Yearning, you will be able to: Prioritize the most promising directions for an AI project; Diagnose errors in a machine learning system; Build ML in complex settings, such as mismatched training/ test sets; Set up an ML project to compare to and/or surpass human - level performance; Know when and how to apply end-to-end learning, transfer learning, and multi-task learning. ...
Machine Learning with Apache Spark Quick Start Guide
Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? Th ...
Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? Th ...
Azure PowerShell Quick Start Guide
As an IT professional, it is important to keep up with cloud technologies and learn to manage those technologies. PowerShell is a critical tool that must be learned in order to effectively and more easily manage many Azure resources. This book is designed to teach you to leverage PowerShell to enable you to perform many day-to-day tasks in Microsoft Azure. Taking you through the basic tasks of installing Azure PowerShell and connecting to Azure, you will learn to properly connect to an Azure tenant with PowerShell. Next, you will dive into tasks such as deploying virtual machines with PowerShell, resizing them, and managing their power states with PowerShell. Then, you will learn how to complete more complex Azure tasks with PowerShell, such as deploying virtual machines from custom images, creating images from existing virtual machines, and creating and managing of data disks. Later, you will learn how to snapshot virtual machines, how to encrypt virtual machines, and how to lev ...
As an IT professional, it is important to keep up with cloud technologies and learn to manage those technologies. PowerShell is a critical tool that must be learned in order to effectively and more easily manage many Azure resources. This book is designed to teach you to leverage PowerShell to enable you to perform many day-to-day tasks in Microsoft Azure. Taking you through the basic tasks of installing Azure PowerShell and connecting to Azure, you will learn to properly connect to an Azure tenant with PowerShell. Next, you will dive into tasks such as deploying virtual machines with PowerShell, resizing them, and managing their power states with PowerShell. Then, you will learn how to complete more complex Azure tasks with PowerShell, such as deploying virtual machines from custom images, creating images from existing virtual machines, and creating and managing of data disks. Later, you will learn how to snapshot virtual machines, how to encrypt virtual machines, and how to lev ...
Julia Programming Projects
Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After ...
Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After ...
Apache Spark 2: Data Processing and Real-Time Analytics
Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. ...
Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. ...
Microsoft Excel 2019 VBA and Macros
Renowned Excel experts Bill Jelen (MrExcel) and Tracy Syrstad explain how to build more powerful, reliable, and efficient Excel spreadsheets. Use this guide to automate virtually any routine Excel task: save yourself hours, days, maybe even weeks. Make Excel do things you thought were impossible, discover macro techniques you won't find anywhere else, and create automated reports that are amazingly powerful. Bill Jelen and Tracy Syrstad help you instantly visualize information to make it actionable; capture data from anywhere, and use it anywhere; and automate the best new features in Excel 2019 and Excel in Office 365. You'll find simple, step-by-step instructions, real-world case studies, and 50 workbooks packed with examples and complete, easy-to-adapt solutions. By reading this book, you will: Quickly master Excel macro development; Work more efficiently with ranges, cells, and formulas; Generate automated reports and quickly adapt them for new requirements; Learn to automate ...
Renowned Excel experts Bill Jelen (MrExcel) and Tracy Syrstad explain how to build more powerful, reliable, and efficient Excel spreadsheets. Use this guide to automate virtually any routine Excel task: save yourself hours, days, maybe even weeks. Make Excel do things you thought were impossible, discover macro techniques you won't find anywhere else, and create automated reports that are amazingly powerful. Bill Jelen and Tracy Syrstad help you instantly visualize information to make it actionable; capture data from anywhere, and use it anywhere; and automate the best new features in Excel 2019 and Excel in Office 365. You'll find simple, step-by-step instructions, real-world case studies, and 50 workbooks packed with examples and complete, easy-to-adapt solutions. By reading this book, you will: Quickly master Excel macro development; Work more efficiently with ranges, cells, and formulas; Generate automated reports and quickly adapt them for new requirements; Learn to automate ...
Python: Advanced Guide to Artificial Intelligence
This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. ...
This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. ...
Artificial Intelligence and Machine Learning Fundamentals
Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! ...
Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! ...
TensorFlow Machine Learning Projects
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits - simplicity, efficiency, and flexibility - of using TensorFlow in various real-world projects. With the help of this book, you'll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem. To start with, you'll get to grips with using TensorFlow for machine learning projects; you'll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification. As you make your way through the book, you'll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative ...
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits - simplicity, efficiency, and flexibility - of using TensorFlow in various real-world projects. With the help of this book, you'll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem. To start with, you'll get to grips with using TensorFlow for machine learning projects; you'll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification. As you make your way through the book, you'll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative ...
Go Machine Learning Projects
Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured. The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate m ...
Go is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code. This book will teach you how to implement machine learning in Go to make programs that are easy to deploy and code that is not only easy to understand and debug, but also to have its performance measured. The book begins by guiding you through setting up your machine learning environment with Go libraries and capabilities. You will then plunge into regression analysis of a real-life house pricing dataset and build a classification model in Go to classify emails as spam or ham. Using Gonum, Gorgonia, and STL, you will explore time series analysis along with decomposition and clean up your personal Twitter timeline by clustering tweets. In addition to this, you will learn how to recognize handwriting using neural networks and convolutional neural networks. Lastly, you'll learn how to choose the most appropriate m ...