The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. And in the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. Machine learning is the automation of discovery - the scientific method on steroids - that enables intelligent robots and computers to program themselves. No field of science today is more important yet more shrouded in mystery. Pedro Domingos, one of the field's leading lights, lifts the veil for the first time to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. Step by step, he assembles a blueprint for the future universal learner - the Master Algorithm - and discusses what it means for you, and for the future of business, science, and society. If data-ism is today's rising philosophy, this book will be its bible. The quest for universal learning is one of the most significant, fascinating, and revolutionary intellectual developments of all time. The Master Algorithm is the essential guide for anyone and everyone wanting to understand not just how the revolution will happen, but how to be at its forefront.
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LibraryThing ReviewUser Review - Paul_S - LibraryThing
Inane verbiage with no educational content. Just constant fawning and endless lists of potential and current applications of learning algorithms. The writing is beyond tiresome. Here's just one ... Read full review
LibraryThing ReviewUser Review - antao - LibraryThing
Machine Learning Made Easier (or NOT!): "The Master Algorithm" by Pedro Domingos Published September 22nd 2015. How can one become an expert in ML? All one needs is a basic background in (multivariate ... Read full review
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Master Algorithm: How the Quest for the Ultimate Learning Machine Will ...
No preview available - 2017