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.

Even the smartest among us can feel inept as we fail to figure out which light switch or oven burner to turn on, or whether to push, pull, or slide a door. The fault, argues this ingenious - even liberating - audiobook, lies not in ourselves, but in product design that ignores the needs of users and the principles of cognitive psychology. The Design of Everyday Things shows that good, usable design is possible. The rules are simple: make things visible, exploit natural relationships that couple function and control, and make intelligent use of constraints.

Jeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.

In Overcomplicated, complexity scientist Samuel Arbesman offers a fresh, insightful field guide to living with complex technologies that defy human comprehension. As technology grows more complex, Arbesman argues, its behavior mimics the vagaries of the natural world more than it conforms to a mathematical model. If we are to survive and thrive in this new age, we must abandon our need for governing principles and rules and accept the chaos.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

Machine learning is changing the world. You use machine learning every day and probably don’t know it. In this audiobook, you will learn how ML grew from a desire to make computers able to learn.

This book is designed to be an introduction to machine learning algorithms for a complete beginner. It starts with an explanation of exactly what machine learning algorithms are and then walks you through the languages and frameworks used to create them. Studying machine learning is considered to be quite challenging due to the impression that special talent is required or some unachievable level of mathematics is needed in order to understand the various algorithms and techniques. But anyone can learn to become a machine learner and put the theory into practice.

In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable. In this groundbreaking audiobook, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines.

Given the large amounts of data we use everyday; whether it is in the web, supermarkets, social media etc., analysis of data has become integral to our daily life. The ability to do so effectively can propel your career or business to great heights. Machine learning is the most effective data analysis tool. While it is a complex topic, it can be broken down into simpler steps, as show in this audiobook. We are using Python, which is a great programming language for beginners. Python is a great language that is commonly used with machine learning.

An exhilarating, elegant memoir and a significant polemic on how computers and algorithms shape our understanding of the world and of who we are. Bitwise is a wondrous ode to the computer languages and codes that captured technologist David Auerbach's imagination.

This bundle includes two audiobooks: Neural Networks and Deep Learning! You will understand the basics of what neural networks are, how they work, and the many tasks you can apply them to. This audiobook will also explain to you in simple layman’s terms the basic foundation and concept of deep learning and how it works.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.

Are you confused about what all the rage behind artificial intelligence is and would like to learn more? This audiobook covers everything from machine learning to robotics and the internet of things. You can use it as a nifty guidebook whenever you come across news headlines that talk about some new advancement in AI by Google or Facebook. By the time you finish listening, you will be aware of what artificial neural networks are, how gradient descent and back propagation work, and what deep learning is.

The goal of this book is simple: provide a perfect insight into data science from scratch. It clearly explains the difference between data science and big data, explaining the concept of big data very concisely and clearly. Operations on data are also very clearly explained in this audiobook. The book is also an ultimate guide to master data mining and data-analytic.

Imagine a world where the difference between man and machine blurs, where the line between humanity and technology fades, and where the soul and the silicon chip unite. This is not science fiction. This is the twenty-first century according to Ray Kurzweil, the “restless genius” (The Wall Street Journal), “ultimate thinking machine” (Forbes), and inventor of the most innovative and compelling technology of our era.