Mastering Machine Learning with Python in Six Steps

Description

This book is your practical guide towards novice to master in machine learning with
Python in six steps. The six steps path has been designed based on the “Six degrees of
separation” theory that states that everyone and everything is a maximum of six steps
away. Note that the theory deals with the quality of connections, rather than their existence. So a great effort has been taken to design eminent, yet simple six steps covering
fundamentals to advanced topics gradually that will help a beginner walk his way from
no or least knowledge of machine learning in Python to all the way to becoming a master
practitioner. This book is also helpful for current Machine Learning practitioners to learn
the advanced topics such as Hyperparameter tuning, various ensemble techniques,
Natural Language Processing (NLP), deep learning, and the basics of reinforcement
learning.

This book will serve as a great resource for learning machine learning concepts and
implementation techniques for the following:

• Python developers or data engineers looking to expand their knowledge or career into the machine learning area.
• A current non-Python (R, SAS, SPSS, Matlab, or any other language) machine learning practitioners looking to expand their implementation skills in Python.
• Novice machine learning practitioners looking to learn advanced topics such as hyperparameter tuning, various ensemble techniques, Natural Language Processing (NLP), deep learning, and basics of reinforcement learning.