<p>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.</p><p>By using concrete examples, minimal theory, and two production-ready Python frameworks鈥擲cikit-Learn and TensorFlow鈥攁uthor Aur茅lien G茅ron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You鈥檒l 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鈥檝e learned, all you need is programming experience to get started.</p><ul><li>Explore the machine learning landscape, particularly neural nets</li><li>Use Scikit-Learn to track an example machine-learning project end-to-end</li><li>Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods</li><li>Use the TensorFlow library to build and train neural nets</li><li>Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning</li><li>Learn techniques for training and scaling deep neural nets</li></ul>

<p>When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it鈥檚 often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.</p><p>Throughout the book, you鈥檒l explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You鈥檒l discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed.</p><p>This book examines:</p><ul><li><b>Storage engines:</b> Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each</li><li><b>Storage building blocks:</b> Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log</li><li><b>Distributed systems:</b> Learn step-by-step how nodes and processes connect and build complex communication patterns</li><li><b>Database clusters:</b> Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency</li></ul>

<b>Authored by 3 Product Managers at Google, Facebook, and Microsoft,聽</b><i>Swipe to Unlock</i>聽is a comprehensive guide on the must-know concepts of technology and business strategy.聽<b>It is a must-read for anyone pursuing product management, design, marketing, consulting or business strategy roles in the tech industry.</b><br /><br />***Swipe to Unlock was updated in 2019 to <b>include over 40 pages of new content</b> to cover the latest developments in the world of tech.***<b> We highly recommend buying our book directly from Amazon rather than a third-party seller as it's the only way to ensure you get the latest version.</b><br /><br />This聽<b>#1 Amazon Business Bestseller won a medal聽</b>from the聽<b>North American Book Awards</b> and has been featured in聽<b>The Wall Street Journal</b>, <b>Forbes</b>,聽and聽<b>Business Insider.聽</b><i>Swipe to Unlock</i> was touted as聽<b>"our generation's Rosetta Stone for enabling anyone to peer into the technology changing everyday life"</b>聽by Jeremy Schifeling.<br /><ul><li>How does Spotify determine what songs to recommend to you?</li><li>How did KaiOS become the third largest mobile operating system in just two years since launching?</li><li>Why does Amazon offer free shipping with Prime if it loses them money?</li><li>How did a single typo take down 20% of the internet?</li><li>Why did Microsoft acquire LinkedIn?</li></ul>By answering real-world questions like this,聽<b><i>Swipe to Unlock</i>聽gives you a peek under the hood of the technology you use every day, decodes tech's biggest buzzwords, and shows you how technology is changing the society we live in for better or for worse.</b><br /><br /><b>Topics Covered:聽</b>Software Development, Business Models & Strategies, Economics, Hacking & Security, Hardware & Robots, The Internet, Cloud Computing, Big Data, Technology Policy, Emerging Markets, Future Trends, and much more!<br /><br /><b>Featured Companies:聽</b>Google, Facebook, Microsoft, Amazon, Apple, Spotify, Uber, WeChat, Yelp, Tinder, Washington Post, Grab, Toyota, GoJek, Samsung, Salesforce, M-Pesa, Quora, KaiOS, Twitter, Tesla, ByteDance, Airbnb, Robinhood, Adobe, Alibaba, Netflix, Paytm, Target, and many more!<br /><br /><b>Unlock the answers you need to ace your tech interviews or become a better-educated digital citizen. Buy Swipe to Unlock today to understand why it's a Top Gifted Book of 2018!</b><br />

<p>What do flashlights, the British invasion, black cats, and seesaws have to do with computers? In CODE, they show us the ingenious ways we manipulate language and invent new means of communicating with each other. And through CODE, we see how this ingenuity and our very human compulsion to communicate have driven the technological innovations of the past two centuries. <br /> Using everyday objects and familiar language systems such as Braille and Morse code, author Charles Petzold weaves an illuminating narrative for anyone who鈥檚 ever wondered about the secret inner life of computers and other smart machines. <br /> It鈥檚 a cleverly illustrated and eminently comprehensible story鈥攁nd along the way, you鈥檒l discover you鈥檝e gained a real context for understanding today鈥檚 world of PCs, digital media, and the Internet. No matter what your level of technical savvy, CODE will charm you鈥攁nd perhaps even awaken the technophile within.

Since<i> Don鈥檛 Make Me Think </i>was first published in 2000, hundreds of thousands of Web designers and developers have relied on usability guru Steve Krug鈥檚 guide to help them understand the principles of intuitive navigation and information design. Witty, commonsensical, and eminently practical, it鈥檚 one of the best-loved and most recommended books on the subject.<br /> <br />Now Steve returns with fresh perspective to reexamine the principles that made<i> Don鈥檛 Make Me Think</i> a classic鈥搘ith updated examples and a new chapter on mobile usability. And it鈥檚 still short, profusely illustrated鈥nd best of all鈥揻un to read.<br /> <br />If you鈥檝e read it before, you鈥檒l rediscover what made <i>Don鈥檛 Make Me Think</i> so essential to Web designers and developers around the world. If you鈥檝e never read it, you鈥檒l see why so many people have said it should be required reading for anyone working on Web sites.<br /> <br /> <br />鈥淎fter reading it over a couple of hours and putting its ideas to work for the past five years, I can say it has done more to improve my abilities as a Web designer than any other book.鈥?lt;br />鈥揓effrey Zeldman, author of Designing with Web Standards <p>聽</p>

<b>AS HEARD ON NPR'S "SCIENCE FRIDAY"</b><b><br /></b><b>Discover the book that Malcolm Gladwell, Susan Cain, Daniel Pink, and Adam Grant want you to read this year, an "accessible, informative, and hilarious" introduction to the weird and wonderful world of artificial intelligence (Ryan North).</b><br />"You look like a thing and I love you" is one of the best pickup lines ever... according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog <i>AI Weirdness</i>. She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans--all to understand the technology that governs so much of our daily lives.<br />We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI <i>really</i>... and how does it solve problems, understand humans, and even drive self-driving cars?<br />Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't. Like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"?<br />In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt--and how they reflect the best and worst of humanity.<br /><i>You Look Like a Thing and I Love You </i>is the perfect book for anyone curious about what the robots in our lives are thinking.<br /><b>"I can't think of a better way to learn about artificial intelligence, and I've never had so much fun along the way." - Adam Grant, <i>New York Times </i>bestselling author of <i>Originals</i></b><b><i><br /></i></b>

<p>Distributed systems have become more fine-grained in the past 10 years, shifting from code-heavy monolithic applications to smaller, self-contained microservices. But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.</p><p>Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You鈥檒l follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.</p><ul><li>Discover how microservices allow you to align your system design with your organization鈥檚 goals</li><li>Learn options for integrating a service with the rest of your system</li><li>Take an incremental approach when splitting monolithic codebases</li><li>Deploy individual microservices through continuous integration</li><li>Examine the complexities of testing and monitoring distributed services</li><li>Manage security with user-to-service and service-to-service models</li><li>Understand the challenges of scaling microservice architectures</li></ul>

<b><i>Longlisted for the National Book Award<br /></i>New York Times <i>Bestseller</i><br /><br />A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life聽鈥?and threaten to rip apart our social fabric</b><br /><br />We live in the age of the algorithm. Increasingly, the decisions that affect our lives鈥攚here we go to school, whether we get a car loan, how much we pay for health insurance鈥攁re being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated.<br /><br />But as Cathy O鈥橬eil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they鈥檙e wrong. Most troubling, they reinforce discrimination: If a poor student can鈥檛 get a loan because a lending model deems him too risky (by virtue of his zip code), he鈥檚 then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a 鈥渢oxic cocktail for democracy.鈥?Welcome to the dark side of Big Data.<br /><br />Tracing the arc of a person鈥檚 life, O鈥橬eil exposes the black box models that shape our future, both as individuals and as a society. These 鈥渨eapons of math destruction鈥?score teachers and students, sort r茅sum茅s, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.<br /><br />O鈥橬eil calls on modelers to take more responsibility for their algorithms and on policy makers to regulate their use. But in the end, it鈥檚 up to us to become more savvy about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.<br /><br />鈥?Longlist for National Book Award (Non-Fiction)<br />鈥?Goodreads, semi-finalist for the 2016 Goodreads Choice Awards (Science and Technology)<br />鈥?Kirkus, Best Books of 2016<br />鈥?<i>New York Times,</i> 100 Notable Books of 2016 (Non-Fiction)<br />鈥?<i>The Guardian</i>, Best Books of 2016<br />鈥?WBUR's "On Point," Best Books of 2016: Staff Picks<br />鈥?Boston Globe, Best Books of 2016, Non-Fiction

<p>How do you detangle a monolithic system and migrate it to a microservice architecture? How do you do it while maintaining business-as-usual? As a companion to Sam Newman鈥檚 extremely popular <i>Building Microservices</i>, this new book details a proven method for transitioning an existing monolithic system to a microservice architecture.</p><p>With many illustrative examples, insightful migration patterns, and a bevy of practical advice to transition your monolith enterprise into a microservice operation, this practical guide covers multiple scenarios and strategies for a successful migration, from initial planning all the way through application and database decomposition. You鈥檒l learn several tried and tested patterns and techniques that you can use as you migrate your existing architecture.</p><ul><li>Ideal for organizations looking to transition to microservices, rather than rebuild</li><li>Helps companies determine whether to migrate, when to migrate, and where to begin</li><li>Addresses communication, integration, and the migration of legacy systems</li><li>Discusses multiple migration patterns and where they apply</li><li>Provides database migration examples, along with synchronization strategies</li><li>Explores application decomposition, including several architectural refactoring patterns</li><li>Delves into details of database decomposition, including the impact of breaking referential and transactional integrity, new failure modes, and more</li></ul>

<p><b>Influence action through data!</b></p> <p>This is not a book. It is a one-of-a-kind immersive learning experience through which you can become鈥攐r teach others to be鈥攁 powerful data storyteller.</p> <p><i>Let鈥檚 practice! </i>helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon best seller <i>storytelling with data</i>鈥檚 foundational lessons, <i>Let鈥檚 practice! </i>delivers fresh content, a plethora of new examples, and over 100 hands-on exercises. Author and data storytelling maven Cole Nussbaumer Knaflic guides you along the path to hone core skills and become a well-practiced data communicator. Each chapter includes:</p> <p>鈼?<b>Practice with Cole:</b> exercises based on real-world examples first posed for you to consider and solve, followed by detailed step-by-step illustration and explanation</p> <p>鈼?<b>Practice on your own:</b> thought-provoking questions and even more exercises to be assigned or worked through individually, without prescribed solutions</p> <p>鈼?<b>Practice at work:</b> practical guidance and hands-on exercises for applying <i>storytelling with data </i>lessons on the job, including instruction on when and how to solicit useful feedback and refine for greater impact</p> <p>The lessons and exercises found within this comprehensive guide will empower you to master鈥攐r develop in others鈥攄ata storytelling skills and transition your work from acceptable to exceptional. By investing in these skills for ourselves and our teams, we can all tell inspiring and influential data stories!</p>