This book introduces ML concepts and implementations of algorithms in Python both from scratch and with libraries. Each chapter of the book is a walkthrough of an industry adopted application. Author Yuxi (Hayden) Liu uses examples to show the mechanics of ML techniques in areas such as exploratory data analysis, feature engineering, classification, regression, clustering, and NLP. This extended and updated edition now includes implementation with libraries including TensorFlow, gensim and Keras. The scikit-learn codes are also fully modernized.

<ASIN:1789616727>

Author: Yuxi (Hayden) Liu
Publisher: Packt Publishing
Date: February 2019
Pages: 382
ISBN: 978-1789616729
Print: 1789616727
Kindle: B07KQ23Q87
Audience: Python developers interested in machine learning
Level: Intermediate
Category: Artificial Intelligence

• Understand the important concepts in machine learning and data science
• Use Python to explore the world of data mining and analytics
• Scale up model training using varied data complexities with Apache Spark
• Delve deep into text and NLP using Python libraries such NLTK and gensim
• Select and build an ML model and evaluate and optimize its performance
• Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

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