Each year about 28 million Americans begin a search for a new job. Millions more live in the age of the permanent job search, their online profiles eternally awaiting a better offer. Job seekers are more mobile and better informed than ever, aspiring to work for employers offering an appealing culture, a robust menu of perks, and opportunities for personal fulfillment and advancement. The result is that millions of applications stream to the handful of companies that regularly top listings of the best companies to work for.

From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

In 1956 two Bell Labs scientists discovered the scientific formula for getting rich. One was mathematician Claude Shannon, neurotic father of our digital age, whose genius is ranked with Einstein's. The other was John L. Kelly Jr., a Texas-born gun-toting physicist. Together they applied the science of information theory - the basis of computers and the Internet - to the problem of making as much money as possible as fast as possible.

In the 18th century, the British minister and mathematician Thomas Bayes devised a theorem that allowed him to assign probabilities to events that had never happened before. It languished in obscurity for centuries until computers came along and made it easy to crunch the numbers. Now, as the foundation of big data, Bayes's formula has become a linchpin of the digital economy. But here's where things get interesting: Bayes's theorem can also be used to lay odds on the existence of extraterrestrial intelligence, and on the biggest question of all: how long will humanity survive?

Technical knowledge alone isn't enough - increase your software development income by leveling up your soft skills Early in his software developer career, John Sonmez discovered that technical knowledge alone isn't enough to break through to the next income level - developers need "soft skills" like the ability to learn new technologies just in time, communicate clearly with management and consulting clients, negotiate a fair hourly rate, and unite teammates and coworkers in working toward a common goal.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

Exploring and explaining a litany of glitches, near misses, and mathematical mishaps involving the internet, big data, elections, street signs, lotteries, the Roman Empire, and an Olympic team, Matt Parker uncovers the bizarre ways math trips us up, and what this reveals about its essential place in our world. Getting it wrong has never been more fun.

As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques.

From the best-selling author of Thinking, Fast and Slow, the co-author of Nudge, and the author of You Are About to Make a Terrible Mistake! comes Noise, a revolutionary exploration of why people make bad judgments, and how to control both noise and cognitive bias.

How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world’s leading practitioners construct and maintain software. This book covers Google’s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization.

Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.

From the visionary head of Google's innovative People Operations comes a groundbreaking inquiry into the philosophy of work - and a blueprint for attracting the most spectacular talent to your business and ensuring that they succeed. "We spend more time working than doing anything else in life. It's not right that the experience of work should be so demotivating and dehumanizing". So says Laszlo Bock, former head of People Operations at the company that transformed how the world interacts with knowledge.

Although software has become easier to build, launching and scaling new products and services remains difficult. Start-ups face daunting challenges entering the technology ecosystem, including stiff competition, copycats, and ineffective marketing channels. Teams launching new products must consider the advantages of “the network effect”, where a product or service’s value increases as more users engage with it. Apple, Google, Microsoft, and other tech giants utilize network effects, and most tech products incorporate them.

While we cannot predict every question that Amazon will ask in an interview, the process is fairly structured. This makes the interview process transparent and easy to prepare for because we know many of the themes they will cover and questions they will ask. Imagine if your teacher in university told you most of the questions that were going to be on the test beforehand - all you would have to do is practice. Consider this book your study guide.

For any task you might want to do, there's a right way, a wrong way, and a way so monumentally complex, excessive, and inadvisable that no one would ever try it. How To is a guide to the third kind of approach. It's full of highly impractical advice for everything from landing a plane to digging a hole.