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The Master Algorithm: How the Quest for the…
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The Master Algorithm: How the Quest for the Ultimate Learning Machine Will…

by Pedro Domingos

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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) Calculus, Linear Algebra, and Probability. ML is math. If one wants to understand the techniques, one has to understand the math. No shortcut. If one wants to start looking into the field of ML, this book is for you. If not, stay well clear.
 
My background is in computer science and software engineering and I've been interested in ML since I can remember. In 2013 I took Andrew NG's ML class at Stanford University (for those of you who want to dive into stuff like this here are mynotes of the class; while learning the needed math can look daunting at first it is actually quite fun once you get into it), and I was never literally the same…After that I made some Python coding to get a feel for the real thing, which I’m still doing to this day.
 
Humans ARE machines, albeit biologically-based. Billions of highly interconnected neurons receiving sensory input, lots of internal feedback, and signals that go out to motors, etc. Emotions, feelings, consciousness, are all just “concepts” we've constructed through a mixture of self-introspection and communicating with other self-introspecting machines (humans).
 
Read on, if learning comes as second nature to you. ( )
  antao | Dec 10, 2016 |
This is a great book about machine learning for both: people who want to know more about it and people who are in this business. Domingos is a great writer with the ability to present complex ideas in easily digestible form. Here you will learn not only what you can do today with machine learning, but also the various philosophical camps, their approaches and finally the limitations of machine learning.

What is interesting about machine learning is that all algorithms in use today are statistical methods developed primarily in the 1960s and 70s. The only negative thing I have to say about this book is that I find some of his optimism a bit unfounded given the limitations of all of these techniques. ( )
  Alex1952 | Aug 28, 2016 |
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[T]here’s a burgeoning, alternative model of programming and computation that sidesteps the limitations of the classic model, embracing uncertainty, variability, self-correction, and overall messiness. It’s called machine learning, and it’s impacted fields as diverse as facial recognition, movie recommendations, real-time trading, and cancer research—as well as all manner of zany experiments, like Google’s image-warping Deep Dream. Yet even within computer science, machine learning is notably opaque. In his new book The Master Algorithm, Pedro Domingos covers the growing prominence of machine learning in close but accessible detail. Domingos’ book is a nontechnical introduction to the subject, but even if it still seems daunting, it’s important to understand how machine learning works, the many forms it can take, and how it’s taking on problems that give traditional computing a great deal of trouble. Machine learning won’t bring us a utopian singularity or a dystopian Skynet, but it will inform an increasing amount of technology in the decades to come.
added by elenchus | editslate.com, David Auerbach (Sep 25, 2015)
 
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Amazon.com Product Description (ISBN 0465065708, Hardcover)


Algorithms increasingly run our lives. They find books, movies, jobs, and dates for us, manage our investments, and discover new drugs. More and more, these algorithms work by learning from the trails of data we leave in our newly digital world. Like curious children, they observe us, imitate, and experiment. 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. He charts a course through machine learning’s five major schools of thought, showing how they turn ideas from neuroscience, evolution, psychology, physics, and statistics into algorithms ready to serve you. 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. A groundbreaking book, 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.

(retrieved from Amazon Fri, 21 Aug 2015 01:01:12 -0400)

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