Beginning Data Science in R 4, 2nd Edition
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R 4, Second Edition details how data science is a combination of statistics, computational science, and machine learning. You'll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. ...
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R 4, Second Edition details how data science is a combination of statistics, computational science, and machine learning. You'll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. This book is based on a number of lecture notes for classes the author has taught on data science and statistical programming using the R programming language. Modern data analysis requires computational skills and usually a minimum of programming. ...
Productive and Efficient Data Science with Python
This book focuses on the Python-based tools and techniques to help you become highly productive at all aspects of typical data science stacks such as statistical analysis, visualization, model selection, and feature engineering. You'll review the inefficiencies and bottlenecks lurking in the daily business process and solve them with practical solutions. Automation of repetitive data science tasks is a key mindset that is promoted throughout the book. You'll learn how to extend the existing coding practice to handle larger datasets with high efficiency with the help of advanced libraries and packages that already exist in the Python ecosystem. The book focuses on topics such as how to measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a data science pipeline for app development. You'll review Python libraries which come in very handy for automating and speeding up the day-to-day tasks. In the end ...
This book focuses on the Python-based tools and techniques to help you become highly productive at all aspects of typical data science stacks such as statistical analysis, visualization, model selection, and feature engineering. You'll review the inefficiencies and bottlenecks lurking in the daily business process and solve them with practical solutions. Automation of repetitive data science tasks is a key mindset that is promoted throughout the book. You'll learn how to extend the existing coding practice to handle larger datasets with high efficiency with the help of advanced libraries and packages that already exist in the Python ecosystem. The book focuses on topics such as how to measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a data science pipeline for app development. You'll review Python libraries which come in very handy for automating and speeding up the day-to-day tasks. In the end ...
Azure Cognitive Services Succinctly
Azure Cognitive Services puts the power of AI and machine learning into the hands of software developers without requiring a PhD or years of experience in the field. With Azure Cognitive Services Succinctly, author Ed Freitas delivers an accessible guide to integrating computer vision, decision-making, speech, and more into your applications to give your apps an edge over the competition, whether you're building for the enterprise or just for fun. ...
Azure Cognitive Services puts the power of AI and machine learning into the hands of software developers without requiring a PhD or years of experience in the field. With Azure Cognitive Services Succinctly, author Ed Freitas delivers an accessible guide to integrating computer vision, decision-making, speech, and more into your applications to give your apps an edge over the competition, whether you're building for the enterprise or just for fun. ...
Data Algorithms with Spark
Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script. With this book, you will: Learn how to select Spark transformations for optimized solutions; Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions(); Understand data partitioning for optimized queries; Build and apply a model using PySpark desig ...
Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script. With this book, you will: Learn how to select Spark transformations for optimized solutions; Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions(); Understand data partitioning for optimized queries; Build and apply a model using PySpark desig ...
Modernizing Your Windows Applications with the Windows App SDK and WinUI
If you're a developer looking to improve and modernize your existing LOB applications to leverage modern Windows features without having to rewrite the entire application from scratch, this book is for you. You'll learn how to modernize your existing Windows Forms, WPF, and UWP applications and enrich them with the latest Windows features. Starting with sample LOB applications that cover common scenarios, you'll learn the differences between various components and then focus on design features for improved visual aspects like accessibility and responsive layouts. The book shows you how to enhance your existing applications using Windows App SDK components and various Windows APIs, resulting in deeper integration with the operating system. You'll be taking a closer look at WinML, which enables Windows applications to evaluate machine learning models offline and leverage the power of your machine, or notifications, to engage with your users in a more effective way. You'll also lear ...
If you're a developer looking to improve and modernize your existing LOB applications to leverage modern Windows features without having to rewrite the entire application from scratch, this book is for you. You'll learn how to modernize your existing Windows Forms, WPF, and UWP applications and enrich them with the latest Windows features. Starting with sample LOB applications that cover common scenarios, you'll learn the differences between various components and then focus on design features for improved visual aspects like accessibility and responsive layouts. The book shows you how to enhance your existing applications using Windows App SDK components and various Windows APIs, resulting in deeper integration with the operating system. You'll be taking a closer look at WinML, which enables Windows applications to evaluate machine learning models offline and leverage the power of your machine, or notifications, to engage with your users in a more effective way. You'll also lear ...
Generic Data Structures and Algorithms in Go
Advance your understanding of generic data structures and algorithms and their applications using Go and the effective use of concurrency. You are invited on a journey that aims to improve your programming and problem-solving skills. This book takes you to the next step by showing how to get your programs to work efficiently as well as correctly. As you explore many data structures and the algorithms and applications associated with them, you'll focus on the trade-offs between speed and storage and the benefits of deploying concurrency when appropriate. This book will demonstrate the huge increases in application performance that are possible. The presentation of classic data structures and techniques of algorithm design (greedy, divide and conquer, branch-and-bound to name a few) provides an essential foundation and toolkit for problem solving. But this book goes further by presenting heuristic algorithms and their implementations for solving computationally intractable combinator ...
Advance your understanding of generic data structures and algorithms and their applications using Go and the effective use of concurrency. You are invited on a journey that aims to improve your programming and problem-solving skills. This book takes you to the next step by showing how to get your programs to work efficiently as well as correctly. As you explore many data structures and the algorithms and applications associated with them, you'll focus on the trade-offs between speed and storage and the benefits of deploying concurrency when appropriate. This book will demonstrate the huge increases in application performance that are possible. The presentation of classic data structures and techniques of algorithm design (greedy, divide and conquer, branch-and-bound to name a few) provides an essential foundation and toolkit for problem solving. But this book goes further by presenting heuristic algorithms and their implementations for solving computationally intractable combinator ...
Agile Visualization with Pharo
Use the Pharo interactive development environment to significantly reduce the cost of creating interactive visualizations. This book shows how Pharo leverages visualization development against traditional frameworks and toolkits. Agile Visualization with Pharo focuses on the Roassal visualization engine and first presents the basic and necessary tools to visualize data, including an introduction to the Pharo programming language. Once you've grasped the basics, you'll learn all about the development environment offered by Roassal. The book provides numerous ready-to-use examples. You'll work on several applications, including visualizing the training phase of reinforcement learning (a powerful machine learning algorithm) and generating software visualizations from GitHub. ...
Use the Pharo interactive development environment to significantly reduce the cost of creating interactive visualizations. This book shows how Pharo leverages visualization development against traditional frameworks and toolkits. Agile Visualization with Pharo focuses on the Roassal visualization engine and first presents the basic and necessary tools to visualize data, including an introduction to the Pharo programming language. Once you've grasped the basics, you'll learn all about the development environment offered by Roassal. The book provides numerous ready-to-use examples. You'll work on several applications, including visualizing the training phase of reinforcement learning (a powerful machine learning algorithm) and generating software visualizations from GitHub. ...
Kubernetes: Up and Running, 3rd Edition
In just five years, Kubernetes has radically changed the way developers and ops personnel build, deploy, and maintain applications in the cloud. With this book's updated third edition, you'll learn how this popular container orchestrator can help your company achieve new levels of velocity, agility, reliability, and efficiency-whether you're new to distributed systems or have been deploying cloud native apps for some time. Brendan Burns, Joe Beda, Kelsey Hightower, and Lachlan Evenson-who have worked on Kubernetes at Google and beyond-explain how this system fits into the life cycle of a distributed application. Software developers, engineers, and architects will learn ways to use tools and APIs to automate scalable distributed systems for online services, machine learning applications, or even a cluster of Raspberry Pi computers. This guide shows you how to: Create a simple cluster to learn how Kubernetes works; Dive into the details of deploying an application using Kubernetes; ...
In just five years, Kubernetes has radically changed the way developers and ops personnel build, deploy, and maintain applications in the cloud. With this book's updated third edition, you'll learn how this popular container orchestrator can help your company achieve new levels of velocity, agility, reliability, and efficiency-whether you're new to distributed systems or have been deploying cloud native apps for some time. Brendan Burns, Joe Beda, Kelsey Hightower, and Lachlan Evenson-who have worked on Kubernetes at Google and beyond-explain how this system fits into the life cycle of a distributed application. Software developers, engineers, and architects will learn ways to use tools and APIs to automate scalable distributed systems for online services, machine learning applications, or even a cluster of Raspberry Pi computers. This guide shows you how to: Create a simple cluster to learn how Kubernetes works; Dive into the details of deploying an application using Kubernetes; ...
Tidy Modeling with R
Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work. RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people. With this book, you will: Learn the steps necessary to build a model from beginning to end; Understand how to use different modeling and feature engineering approaches fluently; Examine the options for avoiding common pitfalls o ...
Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work. RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people. With this book, you will: Learn the steps necessary to build a model from beginning to end; Understand how to use different modeling and feature engineering approaches fluently; Examine the options for avoiding common pitfalls o ...
Hands-On Healthcare Data
Healthcare is the next frontier for data science. Using the latest in machine learning, deep learning, and natural language processing, you'll be able to solve healthcare's most pressing problems: reducing cost of care, ensuring patients get the best treatment, and increasing accessibility for the underserved. But first, you have to learn how to access and make sense of all that data. This book provides pragmatic and hands-on solutions for working with healthcare data, from data extraction to cleaning and harmonization to feature engineering. Author Andrew Nguyen covers specific ML and deep learning examples with a focus on producing high-quality data. You'll discover how graph technologies help you connect disparate data sources so you can solve healthcare's most challenging problems using advanced analytics. You'll learn: Different types of healthcare data: electronic health records, clinical registries and trials, digital health tools, and claims data; The challenges of workin ...
Healthcare is the next frontier for data science. Using the latest in machine learning, deep learning, and natural language processing, you'll be able to solve healthcare's most pressing problems: reducing cost of care, ensuring patients get the best treatment, and increasing accessibility for the underserved. But first, you have to learn how to access and make sense of all that data. This book provides pragmatic and hands-on solutions for working with healthcare data, from data extraction to cleaning and harmonization to feature engineering. Author Andrew Nguyen covers specific ML and deep learning examples with a focus on producing high-quality data. You'll discover how graph technologies help you connect disparate data sources so you can solve healthcare's most challenging problems using advanced analytics. You'll learn: Different types of healthcare data: electronic health records, clinical registries and trials, digital health tools, and claims data; The challenges of workin ...