Easy Machine Learning

Machine Learning is part of most technological processes and is an integral part of modern society. This book is for technically-minded people who need a quick but comprehensive introduction to the wide-ranging subjects of machine learning and statistical data analysis.

Nguyen and Zeigermann use real-world examples to address the following topics:

• Data preparation and import
• Supervised learning
• Feature selection
• Model validation
• Neural networks and deep learning

Using real-world data, you will learn how to set up a typical workflow, from data import and cleansing, to analysis and visualization of the results. The sample code is Python-based and uses the Scikit-learn, Pandas, NumPy, TensorFlow and Keras libraries.

This book will give you the knowledge you need to assess and appraise machine learning approaches, to understand advanced machine learning literature, and enables you to train your own machine learning models.