In the Master Algorithm you will learn about the ultimate goal of Machine Learning, the different families, and how we will most likely reach this goal.
“All knowledge — past, present and future — can be derived from data by a single, universal learning algorithm”
The following is a review of the book The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos
Meet the 5 core families of Machine Learning algorithms by the hand of The Master Algorithm.
The Machine Learning world, can be broadly divided into 5 different continents, each continent representing a specific family of methods or algorithms that differs from the rest either on the paradigm that originates it, on the underlying methods to each family, or on the ways that the algorithms work. Because of this, each of them is good on solving a specific problem, and has a couple of specific use case applications.
However, they also all have one thing in common: discovering hidden insights in data and using these insights to generate some kind of value. The five families mentioned in the previous paragraph are: Bayesians, Connectionists, Evolutionaries, Analogizers, and Symbolists.
The book starts with a small introduction to machine learning, followed by the main motivation of the work of the author: finding an universal machine learning algorithm that can be used to solve any kind of problem. Algorithms that combine two or more of the aforementioned families have been developed already, gathering the virtues of their constituent families, but none of them has managed to unite all of them.
Then each family is described, with their history, pros, cons, and main algorithms. Lastly, Domingos speaks about the upcoming future of AI, describing the virtues and capabilities of this universal algorithm, but largely leaving aside the possible dangers and challenges that were mentioned in the previous books.
You can see the outline of what the book is about on the following TED talk by the author:
Although this text is a very good read even for a non — machine learning practitioner, it is most enjoyable if we do have some kind of knowledge of each family and have used different kinds of algorithms like Naive Bayes, SVMs or Neural Networks at least to some point. Unlike the two previous books, it is quite focused on Machine Learning, however everything is very very well explained with a lot of examples, analogies and diagrams.
“One Algorithm to rule them all, One algorithm to find them, One Algorithm to bring them all and in the darkness bind them, In the Land of Learning where the Data lies”
You can find the book on Amazon. Thanks for reading How to Learn Machine Learning and have a fantastic day!
The Master Algorithm, By Pedro Domingos
- Domingos, Pedro (Author)
- English (Publication Language)
- 352 Pages - 02/13/2018 (Publication Date) - Basic Books (Publisher)
If you liked this book, check out our other non-technical Artificial Intelligence books: you will love them!