Secrets Of Machine Learning: How It Works And What It Means For You


Book Description

Cutting through the mass of technical literature on machine learning and AI and the plethora of fear-mongering books on the rise of killer robots, Secrets of Machine Learning offers a clear-sighted explanation for the informed reader of what this new technology is, what it does, how it works, and why it's so important.The surge in computer processing power along with the sheer quantities of training data available, means machine learning is now possible in ways wholly unthinkable just five years ago. Computers can recognize potential lung cancer better than doctors, detect fraud better than bankers, and create fake video almost impossible to tell from the real thing. And next, they are likely to drive our cars.Journalist and news product manager Tom Kohn gets to the heart of the revolutionary new technology that is developing all around us, explaining with precision how the different facets of machine learning work, how companies are using it, and why it is permeating all parts of society right now. The book guides readers through the arcane science and jargon in a clear and understandable way, but is detailed enough that it doesn't gloss over the hard technical concepts.If you want to know why Siri sometimes misunderstands you, how Netflix recommends your movies, and how machine learning will affect your job — read this book.




Understanding Machine Learning


Book Description

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.




Interpretable Machine Learning


Book Description

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.




Grokking Machine Learning


Book Description

Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you'll build interesting projects with Python, including models for spam detection and image recognition. You'll also pick up practical skills for cleaning and preparing data.







Creators of Intelligence


Book Description

Get your hands on the secret recipe for a rewarding career in data science from 18 AI leaders Purchase of the print or Kindle book includes a free PDF eBook Key Features Gain access to insights and expertise from data science leaders shared in one-on-one interviews Get pragmatic advice on how to become a successful data scientist and data science leader Receive guidance to overcome common pitfalls and challenges and ensure your projects’ success Book DescriptionA Gartner prediction in 2018 led to numerous articles stating that "85% of AI and machine learning projects fail to deliver.” Although it's unclear whether a mass extinction event occurred for AI implementations at the end of 2022, the question remains: how can I ensure that my project delivers value and doesn't become a statistic? The demand for data scientists has only grown since 2015, when they were dubbed the new “rock stars” of business. But how can you become a data science rock star? As a new senior data leader, how can you build and manage a productive team? And what is the path to becoming a chief data officer? Creators of Intelligence is a collection of in-depth, one-on-one interviews where Dr. Alex Antic, a recognized data science leader, explores the answers to these questions and more with some of the world's leading data science leaders and CDOs. Interviews with: Cortnie Abercrombie, Edward Santow, Kshira Saagar, Charles Martin, Petar Veličković, Kathleen Maley, Kirk Borne, Nikolaj Van Omme, Jason Tamara Widjaja, Jon Whittle, Althea Davis, Igor Halperin, Christina Stathopoulos, Angshuman Ghosh, Maria Milosavljevic, Dr. Meri Rosich, Dat Tran, and Stephane Doyen.What you will learn Find out where to start with AI ethics and how to evolve from frameworks to practice Discover tips on building and managing a data science team Receive advice for organizations seeking to build or mature a data science capability Stop beating your head against a brick wall – pick the environment that'll support your success Read stories from successful data leaders as they reflect on the successes and failures in data strategy development Understand how business areas can best work with data science teams to drive business value Who this book is for This book is for a wide range of audience, from people working in the data science industry through to data science leaders and chief data officers. This book will also cater to senior business leaders interested in learning how data and analytics are used to support decision-making in different domains and sectors. Students contemplating a career in artificial intelligence (AI) and the broader data sector will also find this book useful, along with anyone developing and delivering university-level education, including undergraduate, postgraduate, and executive programs.




The Secret of Our Success


Book Description

How our collective intelligence has helped us to evolve and prosper Humans are a puzzling species. On the one hand, we struggle to survive on our own in the wild, often failing to overcome even basic challenges, like obtaining food, building shelters, or avoiding predators. On the other hand, human groups have produced ingenious technologies, sophisticated languages, and complex institutions that have permitted us to successfully expand into a vast range of diverse environments. What has enabled us to dominate the globe, more than any other species, while remaining virtually helpless as lone individuals? This book shows that the secret of our success lies not in our innate intelligence, but in our collective brains—on the ability of human groups to socially interconnect and learn from one another over generations. Drawing insights from lost European explorers, clever chimpanzees, mobile hunter-gatherers, neuroscientific findings, ancient bones, and the human genome, Joseph Henrich demonstrates how our collective brains have propelled our species' genetic evolution and shaped our biology. Our early capacities for learning from others produced many cultural innovations, such as fire, cooking, water containers, plant knowledge, and projectile weapons, which in turn drove the expansion of our brains and altered our physiology, anatomy, and psychology in crucial ways. Later on, some collective brains generated and recombined powerful concepts, such as the lever, wheel, screw, and writing, while also creating the institutions that continue to alter our motivations and perceptions. Henrich shows how our genetics and biology are inextricably interwoven with cultural evolution, and how culture-gene interactions launched our species on an extraordinary evolutionary trajectory. Tracking clues from our ancient past to the present, The Secret of Our Success explores how the evolution of both our cultural and social natures produce a collective intelligence that explains both our species' immense success and the origins of human uniqueness.




A First Course in Machine Learning


Book Description

Introduces the main algorithms and ideas that underpin machine learning techniques and applications Keeps mathematical prerequisites to a minimum, providing mathematical explanations in comment boxes and highlighting important equations Covers modern machine learning research and techniques Includes three new chapters on Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models Offers Python, R, and MATLAB code on accompanying website: http://www.dcs.gla.ac.uk/~srogers/firstcourseml/"




Ultralearning


Book Description

Now a Wall Street Journal bestseller. Learn a new talent, stay relevant, reinvent yourself, and adapt to whatever the workplace throws your way. Ultralearning offers nine principles to master hard skills quickly. This is the essential guide to future-proof your career and maximize your competitive advantage through self-education. In these tumultuous times of economic and technological change, staying ahead depends on continual self-education—a lifelong mastery of fresh ideas, subjects, and skills. If you want to accomplish more and stand apart from everyone else, you need to become an ultralearner. The challenge of learning new skills is that you think you already know how best to learn, as you did as a student, so you rerun old routines and old ways of solving problems. To counter that, Ultralearning offers powerful strategies to break you out of those mental ruts and introduces new training methods to help you push through to higher levels of retention. Scott H. Young incorporates the latest research about the most effective learning methods and the stories of other ultralearners like himself—among them Benjamin Franklin, chess grandmaster Judit Polgár, and Nobel laureate physicist Richard Feynman, as well as a host of others, such as little-known modern polymath Nigel Richards, who won the French World Scrabble Championship—without knowing French. Young documents the methods he and others have used to acquire knowledge and shows that, far from being an obscure skill limited to aggressive autodidacts, ultralearning is a powerful tool anyone can use to improve their career, studies, and life. Ultralearning explores this fascinating subculture, shares a proven framework for a successful ultralearning project, and offers insights into how you can organize and exe - cute a plan to learn anything deeply and quickly, without teachers or budget-busting tuition costs. Whether the goal is to be fluent in a language (or ten languages), earn the equivalent of a college degree in a fraction of the time, or master multiple tools to build a product or business from the ground up, the principles in Ultralearning will guide you to success.




Artificial Intelligence


Book Description

The applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and - not least - on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. In this Very Short Introduction , Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.