This book assumes that you know close to nothing about Machine
Learning. Its goal is to give you the concepts, the intuitions, and the tools
you need to actually implement programs capable of learning
We will cover a large number of techniques, from the simplest and most
commonly used (such as linear regression) to some of the Deep Learning
techniques that regularly win competitions.
Rather than implementing our own toy versions of each algorithm, we will
be using actual production-ready Python frameworks:
Scikit-Learn is very easy to use, yet it implements many Machine
Learning algorithms efficiently, so it makes for a great entry point to
learn Machine Learning.
TensorFlow is a more complex library for distributed numerical
computation using data flow graphs. It makes it possible to train and
run very large neural networks efficiently by distributing the
computations across potentially thousands of multi-GPU servers.
TensorFlow was created at Google and supports many of their large-
scale Machine Learning applications.