Over the past few years, incremental developments in core engineering practices for software development have created the foundations for rethinking how architecture changes over time, along with ways to protect important architectural characteristics as it evolves. This practical guide ties those parts together with a new way to think about architecture and time.

    From economic development, to healthcare, to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this bias, in time, money, and often with their lives.Celebrated feminist advocate Caroline Criado Perez investigates the shocking root cause of gender inequality and research in Invisible Women​, diving into women’s lives at home, the workplace, the public square, the doctor’s office, and more. Built on hundreds of studies in the US, the UK, and around the world, and written with energy, wit, and sparkling intelligence, this is a groundbreaking, unforgettable exposé that will change the way you look at the world.

    Through four years of groundbreaking research, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance—and what drives it—using rigorous statistical methods. This book presents both the findings and the science behind that research. Readers will discover how to measure the performance of their teams, and what capabilities they should invest in to drive higher performance.

    In Dataclysm, Christian Rudder uses it to show us who we truly are.   For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.   In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.   Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.

    In 2013, the New York Times published an obituary for Yvonne Brill. It began: “She made a mean beef stroganoff, followed her husband from job to job, and took eight years off from work to raise three children.” It wasn’t until the second paragraph that readers discovered why the Times had devoted several hundred words to her life: Brill was a brilliant rocket scientist who invented a propulsion system to keep communications satellites in orbit, and had recently been awarded the National Medal of Technology and Innovation. Among the questions the obituary—and consequent outcry—prompted were, Who are the role models for today’s female scientists, and where can we find the stories that cast them in their true light?      Headstrong delivers a powerful, global, and engaging response. Covering Nobel Prize winners and major innovators, as well as lesser-known but hugely significant scientists who influence our every day, Rachel Swaby’s vibrant profiles span centuries of courageous thinkers and illustrate how each one’s ideas developed, from their first moment of scientific engagement through the research and discovery for which they’re best known. This fascinating tour reveals these 52 women at their best—while encouraging and inspiring a new generation of girls to put on their lab coats.

    It is one of the fastest growing companies in history, an essential part of the social life not only of teenagers but hundreds of millions of adults worldwide. As Facebook spreads around the globe, it creates surprising effects—even becoming instrumental in political protests from Colombia to Iran. Veteran technology reporter David Kirkpatrick had the full cooperation of Facebook’s key executives in researching this fascinating history of the company and its impact on our lives. Kirkpatrick tells us how Facebook was created, why it has flourished, and where it is going next. He chronicles its successes and missteps, and gives readers the most complete assessment anywhere of founder and CEO Mark Zuckerberg, the central figure in the company’s remarkable ascent. This is the Facebook story that can be found nowhere else. How did a nineteen-year-old Harvard student create a company that has transformed the Internet and how did he grow it to its current enormous size? Kirkpatrick shows how Zuckerberg steadfastly refused to compromise his vision, insistently focusing on growth over profits and preaching that Facebook must dominate (his word) communication on the Internet. In the process, he and a small group of key executives have created a company that has changed social life in the United States and elsewhere, a company that has become a ubiquitous presence in marketing, altering politics, business, and even our sense of our own identity. This is the Facebook Effect.

    It has found adherents in Silicon Valley billionaires Ray Kurzweil and Peter Diamandis. Google has entered the picture, establishing a bio-tech subsidiary aimed at solving the problem of aging.In To Be a Machine, journalist Mark O'Connell takes a headlong dive into this burgeoning movement. He travels to the laboratories, conferences, and basements of today's foremost transhumanists, where he's presented with the staggering possibilities and moral quandaries of new technologies like mind uploading, artificial superintelligence, cryonics, and device implants.A contributor to Slate, The New Yorker, and The New York Times Magazine, O'Connell serves as a sharp and lively guide to the outer limits of technology in the twenty first century. In investigating what it means to be a machine, he offers a surprising, singular meditation on what it means to be human."

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    Gates says, "we can work on a local, national, and global level to build the technologies, businesses, and industries to avoid the worst impacts of climate change." His interest in climate change is a natural outgrowth of the efforts by his foundation to reduce poverty and disease. Climate change, according to Gates, will have the biggest impact on the people who have done the least to cause it. As a technologist, he has seen first-hand how innovation can change the world. By investing in research, inventing new technologies, and by deploying them quickly at large scale, Gates believes climate change can be addressed in meaningful ways. According to Gates, "to prevent the worst effects of climate change, we have to get to net-zero emissions of greenhouse gases. This problem is urgent, and the debate is complex, but I believe we can come together to invent new carbon-zero technologies, deploy the ones we have, and ultimately avoid a climate catastrophe."

    Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

    You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples--ready for immediate application to your next graph or presentation.Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data--Storytelling with Data will give you the skills and power to tell it!

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    In this one-of-a-kind text, author V. Anton Spraul breaks down the ways that programmers solve problems and teaches you what other introductory books often ignore: how to Think Like a Programmer. Each chapter tackles a single programming concept, like classes, pointers, and recursion, and open-ended exercises throughout challenge you to apply your knowledge. You'll also learn how to:Split problems into discrete components to make them easier to solve Make the most of code reuse with functions, classes, and libraries Pick the perfect data structure for a particular job Master more advanced programming tools like recursion and dynamic memory Organize your thoughts and develop strategies to tackle particular types of problems Although the book's examples are written in C++, the creative problem-solving concepts they illustrate go beyond any particular language; in fact, they often reach outside the realm of computer science. As the most skillful programmers know, writing great code is a creative art—and the first step in creating your masterpiece is learning to Think Like a Programmer.

    Why is glass see-through? What makes elastic stretchy? Why does a paper clip bend? Why does any material look and behave the way it does? These are the sorts of questions that Mark Miodownik a globally-renowned materials scientist has spent his life exploring In this book he examines the materials he encounters in a typical morning, from the steel in his razor and the graphite in his pencil to the foam in his sneakers and the concrete in a nearby skyscraper.