Machine learning is not a new concept for the all of us. It has been around for decades and has been witnessed since the 1990's when Amazon first introduced a new "Recommended for you " section for all its users that displayed more personalized results. From searching anything on Google to the suggested pages that we get on Facebook, what's behind all of this is Machine Learning.
In other words, these sites know a lot about us but can only predict by looking at our previous clicks and not by looking at the big picture of us.
Now let's suppose that an algorithm knows what we are searching for on Google, or buying on Amazon and what we are watching on Netflix. Now, this algorithm knows a lot about us and also has a better and a more complete picture of us.
And this "Master Algorithm" acts as the heart of this work and acts as the best source to gain interest in this field and get yourself introduced to the concepts in Data Science and machine learning.
About the Book:
This book aims at generating interest from people outside the field and explains how more and more algorithms work by learning from the trails of data that we leave in the digital world that surrounds us and are guided by how we define them and ultimately program them.
The premise of the book is: At 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.
To believe that a single algorithm will be able to make predictions in any problem may be like looking for one theorem in mathematics that solves all problems.
Machine Learning is the automation of Discovery-A scientific method on steroids- that allows robots and computers to make predictions for new observations in the world based on previously known observations. Yet, again based on how we program them.
The premise of the book seems to be compelling, but the real value it holds is in how well each major Learning Algorithm is Described and simultaneously coupled with Real life and identifiable use-case examples.
On balance, the book serves to open the reader's mind to how today’s technology works and how much computers do to make their lives better.
About the Author
Pedro Domingos is presently a Professor at University of Washington. He is a researcher in machine learning and known for Markov logic network enabling uncertain inference. Domingos received an undergraduate degree and M.S. from Instituto Superior Técnico (IST). And then at University of California, Irvine, he received an M.S. and Ph.D. He has made significant contributions to the field of machine learning and to the unification of first-order logic and probability.
The Quest for the Master Algorithm | Pedro Domingos | TEDxUofW
Video Source: TEDx Talks