Artificial Intelligence Machine Learning

According to Forbes, 400 million workers could be displaced globally because of AI. But there is good news. In my book, Tomorrow’s Artificial Intelligence, I will demystify AI’s impact on jobs and empower you to navigate the changing landscape with confidence.

We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.

Artificial intelligence is changing our world faster than we can imagine, and it will impact every area of our lives. And this is happening whether we like it or not. You might have heard that many jobs will be replaced by automation and robots, but did you also know that at the same time a huge number of new jobs will be created by AI? This book covers many fascinating and timely topics related to artificial intelligence, including: self-driving cars, robots, chatbots, and how AI will impact the job market, business processes, and entire industries, just to name a few.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.

Take a data-first and use-case-driven approach with Low-Code AI to understand machine learning and deep learning concepts. This hands-on guide presents three problem-focused ways to learn no-code ML using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. In each case, you'll learn key ML concepts by using real-world datasets with realistic problems.

Longlisted for the Financial Times Business Book of the Year The "rich and gripping" true story of the first time machines came for human jobs—and how the Luddite uprising explains the power, threat, and toll of big tech and AI today (Naomi Klein) The most urgent story in modern tech begins...

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.

A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives and how we can shape the way they impact us.

Are you fascinated by apps like Microsoft’s ChatGPT and Google’s Gemini but unsure how you can utilize them to their full potential? Have you wondered how ChatGPT could help your writing, editing, and even gaming? Understanding and integrating Generative AI into your daily life may seem daunting, but it's not as difficult as you might think. In fact, with the right guide, anyone can harness the power of AI.

The deep-learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep-learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

Coaches, Wellness Experts, and Entrepreneurs—Write Your Book Faster, Easier with AI! Struggling to find time or the right approach to writing your book? Stop the overwhelm—ChatGPT AI makes book writing faster, easier, and smarter than ever! The AI revolution is here! This book reveals a 9-step formula to write, publish, and launch a client-attraction book—without losing your unique voice and authenticity.

This audiobook will help you get ready for the changes coming in the years ahead. Listen now. Packed with expert insights, the book addresses critical questions: How will AI alter employment, education, and global geopolitics? What ethical dilemmas will arise as humans interlace with AI through cyborgs and synthetic biology? Can we prepare for superintelligence and its utopian—or dystopian—outcomes?

Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this audiobook is for you. Artificial intelligence, machine learning, and deep learning are powerful data tools that can help improve businesses. Artificial Intelligence, Machine Learning, and Deep Learning are amazing tools when you want to use data in an effective manner. Data is important to many different areas in life, so it’s important that you know how to use it.

A "fascinating book" that will revolutionize our understanding of the brain and the future of AI (Financial Times) For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered...

If you want to learn about artificial intelligence without having to go through a boring textbook, then pay attention....

The ability to hack AI and the technology industry's lack of effort to secure it is thought by experts to be the biggest unaddressed technology issue of our time. Hacking Artificial Intelligence sheds light on these hacking risks, explaining them to those who can make a difference. This book is the first-ever layman's guide to the new world of hacking AI and introduces the field to thousands of people who should be aware of these risks. From a security perspective, AI is today where the internet was thirty years ago. It is wide open and can be exploited.

It’s said that filling the observable universe with an infinite number of monkeys on infinite typewriters and letting them type for an infinite amount of time would eventually produce Shakespeare’s works. However, what would happen if we applied the infinite monkey theorem to computer programs capable of learning and evolution? Would a thousand such smart machines thrown together and allowed to evolve undisturbed produce a human mind or something much greater? Well, scientists decided to give it a go and see what happened.

Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models.

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning.

Sensationalism about AI has reached new heights, and getting a useful understanding of it has never been more important. AI will extend and accelerate thinking, delivering unprecedented abundance. But it will also require us to navigate a path of challenges ranging from today’s issues of bias, privacy, and explainability, to job displacement through automation, and a future coexistence with superintelligent machines. This book is the roadmap to that path.