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What are the Best Books for Machine Learning?

Published on 21 July 18

Machine learning requires the perfect balance of Engineering and Artificial Intelligence, with the proper hold on the subject matter of each. When one plans on pursuing their career ahead by meaning to excel in Machine Learning, it must be kept in mind, that the grip in the basic concepts needs to be strong enough to teach who comes under you, and flexible enough to absorb new concepts. All these points come handy in a person if he/she has been firm in understanding the concepts of Math, Programming, and Domain knowledge, according to professors and other experts of this subject matter.

The importance of Mathematics is for building the new and innovative designs of machines, as there are many already built, what Is needed is no longer machines, but machines with new ideas, and concepts instilled in it. For the following purpose there needs to be the proper understanding of the interior of machines, the sub-branches of Math like Linear Algebra, Probability Theory, Optimization and Calculus suffices the knowledge needed for that purpose.

Programming, on the other hand, is used to bring and make up plans for creating new models of machines. Although the tension is released a bit when on learning only a few languages of Programming the planner can design new models. Python is best for beginners, and even for advanced learners, R is good but has slow run time, Julia is mostly suggested these days for it being new consisting of limited libraries, it is fast and easy, C++ is difficult but precise in getting results.

Machine modelling is seen as an art, which gets better by practice and reading lots of papers and understanding the techniques and tricks of Math, the concept of Programming through the ML/DL, rather than vice-versa. The following books are recommended by many experts for the building of basic concepts regarding Machine learning to Building new and innovative plans for future machines.
This books by Peter Norvig consists of the up-to-date case studies of AI programming. It has the basic concepts with respect to the machine learning; hence people with very bleak knowledge of programming are advised not to refer the book, instead use something for understanding coding better before taking this book up. It is a 900+ paged book, with detailed descriptions regarding AI, and is seen as the best guide for the subject matter.