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# Python Machine Learning

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Link to the GitHub Repository containing the code examples and additional material: https://github.com/rasbt/python-machi...

Many of the most innovative breakthroughs and exciting new technologies can be attributed to applications of machine learning. We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine ...more

Many of the most innovative breakthroughs and exciting new technologies can be attributed to applications of machine learning. We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine ...more

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Paperback, 454 pages

Published
October 1st 2015
by Packt Publishing
(first published September 23rd 2015)

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It gives the mathematical definitions of popular machine learning algorithms and shows you how to implement them. Then it explains how to use them with scikit-learn which has much more efficient implementations.

What is great is that this book has chapters on data cleaning, what to do with missing data, etc. Compliments greatly the Andrew Ng's ML course which lacked lectures about all of these things.

I ...more

Textbooks in computer science in general, and machine learning in particular, have to walk a delicate line. At one level of high abstraction, everything is mathematical proofs. At a level of low-level cookbookls, it's a matter of just plugging and chugging, treating code as magical invocations without getting at the why. Raschka's book hits the sweet spot between the two exactly, explaining the underlying math, how that math is represented in ...more

This excellent book is a practical introduction to ML using the Python programming language, along with relevant components of Python’s rich ...more

I found it to have a great balance between the theoretical math and implementation in Python; the split is somewhere around 20/80 in favour of implementation and actually using the algorithms on real data-sets. If you are trying to get a good understanding of the theory, then this book is a good starting point but you will most definitely need ...more

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Some of my greatest passions are "Data Science" and machine learning. I enjoy everything that involves working with data: The discovery of interesting patterns and coming up with insightful conclusions using techniques from the fields of data mining and machine learning for predictive modeling.

I am a big advocate of working in teams and the concept of "open source." In my opinion, it is a positive ...more

I am a big advocate of working in teams and the concept of "open source." In my opinion, it is a positive ...more

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