Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks - Scikit-Learn and TensorFlow - author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets; Use Scikit-Learn to track an example machine-learning project end-to-end; Explore several training models, including support vector machines, deci ...
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks - Scikit-Learn and TensorFlow - author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets; Use Scikit-Learn to track an example machine-learning project end-to-end; Explore several training models, including support vector machines, deci ...
Practical Time Series Analysis
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 ...
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 ...
Building Machine Learning Powered Applications
Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). 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 - including experienced practitioners and novices alike - will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Define your product goal and set up ...
Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). 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 - including experienced practitioners and novices alike - will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Define your product goal and set up ...
The Customer-Driven Culture: A Microsoft Story
If you're striving to make products and services that your customers will love, then you'll need a customer-driven organization. As companies transform their businesses to meet the demands of the digital age, they find themselves grappling with uniquely human challenges. Organizational knowledge becomes siloed, employees move to safeguard their expertise, and customer data creates polarization and infighting between teams. All of these challenges widen the distance between the people who make your products and the customers who use them. To meet today's challenges, companies need to do more than build processes for customer-driven products. They need to create a customer-driven culture. With the help of his friend and mentor Monty Hammontree, Travis Lowdermilk takes readers through the cultural transformation of the Developer Division at Microsoft. This book shows readers how to "hack" their culture and reduce the distance between them and their customers' needs. It's a uniquely ...
If you're striving to make products and services that your customers will love, then you'll need a customer-driven organization. As companies transform their businesses to meet the demands of the digital age, they find themselves grappling with uniquely human challenges. Organizational knowledge becomes siloed, employees move to safeguard their expertise, and customer data creates polarization and infighting between teams. All of these challenges widen the distance between the people who make your products and the customers who use them. To meet today's challenges, companies need to do more than build processes for customer-driven products. They need to create a customer-driven culture. With the help of his friend and mentor Monty Hammontree, Travis Lowdermilk takes readers through the cultural transformation of the Developer Division at Microsoft. This book shows readers how to "hack" their culture and reduce the distance between them and their customers' needs. It's a uniquely ...
JavaScript Everywhere
JavaScript is the little scripting language that could. Once used chiefly to add interactivity to web browser windows, JavaScript is now a primary building block of powerful and robust applications. In this practical book, new and experienced JavaScript developers will learn how to use this language to create APIs as well as web, mobile, and desktop applications. Author and engineering leader Adam D. Scott covers technologies such as Node.js, GraphQL, React, React Native, and Electron. Ideal for developers who want to build full stack applications and ambitious web development beginners looking to bootstrap a startup, this book shows you how to create a single CRUD-style application that will work across several platforms. Explore GraphQL's simple process for querying data; Learn about shared authentication for APIs, web apps, and native applications; Build performant web applications with React and Styled Components; Use React Native to write cross-platform applications for iOS ...
JavaScript is the little scripting language that could. Once used chiefly to add interactivity to web browser windows, JavaScript is now a primary building block of powerful and robust applications. In this practical book, new and experienced JavaScript developers will learn how to use this language to create APIs as well as web, mobile, and desktop applications. Author and engineering leader Adam D. Scott covers technologies such as Node.js, GraphQL, React, React Native, and Electron. Ideal for developers who want to build full stack applications and ambitious web development beginners looking to bootstrap a startup, this book shows you how to create a single CRUD-style application that will work across several platforms. Explore GraphQL's simple process for querying data; Learn about shared authentication for APIs, web apps, and native applications; Build performant web applications with React and Styled Components; Use React Native to write cross-platform applications for iOS ...
Architecting for Scale, 2nd Edition
Every day, companies struggle to scale critical applications. As traffic volume and data demands increase, these applications become more complicated and brittle, exposing risks and compromising availability. With the popularity of software as a service, scaling has never been more important. Updated with an expanded focus on modern architecture paradigms such as microservices and cloud computing, this practical guide provides techniques for building systems that can handle huge quantities of traffic, data, and demand—without affecting the quality your customers expect. Architects, managers, and directors in engineering and operations organizations will learn how to build applications at scale that run more smoothly and reliably to meet the needs of customers. Learn how scaling affects the availability of your services, why that matters, and how to improve it; Dive into a modern service-based application architecture that ensures high availability and reduces the effects of ser ...
Every day, companies struggle to scale critical applications. As traffic volume and data demands increase, these applications become more complicated and brittle, exposing risks and compromising availability. With the popularity of software as a service, scaling has never been more important. Updated with an expanded focus on modern architecture paradigms such as microservices and cloud computing, this practical guide provides techniques for building systems that can handle huge quantities of traffic, data, and demand—without affecting the quality your customers expect. Architects, managers, and directors in engineering and operations organizations will learn how to build applications at scale that run more smoothly and reliably to meet the needs of customers. Learn how scaling affects the availability of your services, why that matters, and how to improve it; Dive into a modern service-based application architecture that ensures high availability and reduces the effects of ser ...
TinyML
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size - small enough to run on a microcontroller. With this practical book you'll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures; Work with Arduino and ultra-low-power microcontrollers; Learn the essentials of ML and how to train your own models; Train models to understand audio, image, and accelerometer data; Explore T ...
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size - small enough to run on a microcontroller. With this practical book you'll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures; Work with Arduino and ultra-low-power microcontrollers; Learn the essentials of ML and how to train your own models; Train models to understand audio, image, and accelerometer data; Explore T ...
Designing Interfaces, 3rd Edition
Designing good application interfaces isn't easy now that companies need to create compelling, seamless user experiences across an exploding number of channels, screens, and contexts. In this updated third edition, you'll learn how to navigate through the maze of design options. By capturing UI best practices as design patterns, this best-selling book provides solutions to common design problems. You'll learn patterns for mobile apps, web applications, and desktop software. Each pattern contains full-color examples and practical design advice you can apply immediately. Experienced designers can use this guide as an idea sourcebook, and novices will find a road map to the world of interface and interaction design. Understand your users before you start designing; Build your software's structure so it makes sense to users; Design components to help users complete tasks on any device; Learn how to promote wayfinding in your software; Place elements to guide users to information and ...
Designing good application interfaces isn't easy now that companies need to create compelling, seamless user experiences across an exploding number of channels, screens, and contexts. In this updated third edition, you'll learn how to navigate through the maze of design options. By capturing UI best practices as design patterns, this best-selling book provides solutions to common design problems. You'll learn patterns for mobile apps, web applications, and desktop software. Each pattern contains full-color examples and practical design advice you can apply immediately. Experienced designers can use this guide as an idea sourcebook, and novices will find a road map to the world of interface and interaction design. Understand your users before you start designing; Build your software's structure so it makes sense to users; Design components to help users complete tasks on any device; Learn how to promote wayfinding in your software; Place elements to guide users to information and ...
Python for DevOps
Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today's most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you'll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language; How to automate text, write command-line tools, and automate the filesystem; Linux utilities, package management, build syst ...
Much has changed in technology over the past decade. Data is hot, the cloud is ubiquitous, and many organizations need some form of automation. Throughout these transformations, Python has become one of the most popular languages in the world. This practical resource shows you how to use Python for everyday Linux systems administration tasks with today's most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you'll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide. Python foundations, including a brief introduction to the language; How to automate text, write command-line tools, and automate the filesystem; Linux utilities, package management, build syst ...
gRPC: Up and Running
Get a comprehensive understanding of gRPC fundamentals through real-world examples. With this practical guide, you'll learn how this high-performance interprocess communication protocol is capable of connecting polyglot services in microservices architecture, while providing a rich framework for defining service contracts and data types. Complete with hands-on examples written in Go, Java, Node, and Python, this book also covers the essential techniques and best practices to use gRPC in production systems. Authors Kasun Indrasiri and Danesh Kuruppu discuss the importance of gRPC in the context of microservices development. ...
Get a comprehensive understanding of gRPC fundamentals through real-world examples. With this practical guide, you'll learn how this high-performance interprocess communication protocol is capable of connecting polyglot services in microservices architecture, while providing a rich framework for defining service contracts and data types. Complete with hands-on examples written in Go, Java, Node, and Python, this book also covers the essential techniques and best practices to use gRPC in production systems. Authors Kasun Indrasiri and Danesh Kuruppu discuss the importance of gRPC in the context of microservices development. ...