This 2nd edition covers everything you need to begin writing programs, going logically through the development cycle from initial design and testing to deployment and live iteration. Dan Gookin covers the do's and don'ts of good clean writing and how to produce the basic―and not-so-basic―building blocks of source code.

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This book begins by introducing you to the SQL portfolio in Azure and takes you through SQL Server IaaS scenarios. Authors Joseph D'Antoni et al then go on to explain the factors that you need to consider while choosing an OS for SQL Server in Azure VMs. The authors also explore different VM options and deployment choices for IaaS and understand platform availability, migration tools, and best practices in Azure.

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This book examines the impact intelligent technology will have on humanity. International human rights attorney Flynn Coleman argues that it is critical that we instill values, ethics, and morals into our robots, algorithms, and other forms of AI. Equally important, we need to develop and implement laws, policies, and oversight mechanisms to protect us from tech’s potential threats.

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This book covers the essential skills needed to quickly design, build, and deploy quality web APIs that are robust, reliable, and resilient. Author Mike Amundsen starts from initial design through prototyping and implementation to deployment of mission-critical APIs. The book includes more than a dozen open-source utilities and common programming patterns you can apply right away. It also covers the skills needed to create RESTful HTTP-based APIs

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This is a no-fluff guide to C# 8.0 for programmers at all levels of experience. Well known author Mark Michaelis presents a tutorial and reference for the entire language. This edition adds discussions of null reference types, indices and ranges, static local functions, and enhanced pattern matching. The book includes key C# 8.0 enhancements, succinct examples to illustrate key constructs, and new coding guidelines for minimizing bugs and writing code thats easier to evolve.

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Expose your kids to the world of data! Making the claim "By Real Data Scientists, For Future Data Scientists" author Rikin Mathur follows Data Science Dolphin as she navigates the ABCs to learn about Data Science. Along the way, she meets a few friends such as Analyst Armadillo, Engineer Elephant, and Z-Score Zebra. Together they learn about Histograms, Joint Probability, and even Machine Learning.

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The Raspberry Pi makes an ideal match for the Internet of Things. But to put it to good use in IoT you need two areas of expertise, electronics and programming and because of the way hardware and software engineering tend to occupy separate niches you may need help with combining the two. This expanded second Edition has been brought up-to-date and focuses mainly on the Pi 4 and the Pi Zero. There is new material on the recently introduced GPIO character driver and using the Pi 4’s additional ports and scheduling.

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This is a tutorial on writing, deploying, and running applications in Azure. In it, author Iain Foulds introduces Azure through 21 short lessons that give real-world experience. Each lesson includes a hands-on lab to try out and lock in the new skills. This fully revised new edition covers core changes to the Azure UI, new Azure features, Azure containers, and the upgraded Azure Kubernetes Service.

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The Simulmatics Corporation, launched during the Cold War, mined data, targeted voters, manipulated consumers, destabilized politics, and disordered knowledge―decades before Facebook, Google, and Cambridge Analytica. Jill Lepore, author of These Truths, came across the company’s papers in MIT’s archives and set out to tell this forgotten history, the long-lost backstory to the methods and mindset of Silicon Valley.

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Intended as "A beginner's guide to getting up and running with deep learning from scratch using Python", this book is for those who already have the basic mathematical and programming knowledge required to get started. Dr. Pablo Rivas begins with a basic overview of machine learning, setting up popular Python frameworks, and preparing data by cleaning and preprocessing it for deep learning, before going on to explore neural networks. Later sections cover hands-on training single and multiple layers of neurons, as well as popular neural network architectures such as CNNs, RNNs, AEs, VAEs, and GANs with the help of simple examples.

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With the subtitle "Using Data to Make Good Things Happen",  this is an exploration of the application of analytics to real-world problems and situations. Covering fields as diverse as sports, finance, politics, healthcare, and business, Wayne L. Winston bridges the gap between the world of data analytics and the concrete problems it solves. The questions considered range from "What's wrong with the NFL QB rating?" to "What caused the Crash of 2008?" 

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Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction examines all the major settings, including stochastic, adversarial, and Bayesian frameworks. Tor Lattimore and Csaba Szepesvári focus on both mathematical intuition and carefully worked proofs. 

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