16. Machine Learning

In this chapter you will learn the basic concepts of classical machine learning and apply these concepts to datasets.

Notes compiled from:

1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 3rd Edition by Aurélien Géron

2. Machine Learning with Python for Everyone (Addison-Wesley Data & Analytics Series) 1st Edition by Mark Fenner

3. Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python by Sebastian Raschka (Author), Yuxi (Hayden) Liu (Author), Vahid Mirjalili (Author), Dmytro Dzhulgakov (Foreword)

4. Data Science Interview Mastery : How to build a Career in Data Science , Fundamentals of Data Structures, Machine Learning, and Best 95 Interview Questions and Answers Asked by Top Tech Firms by Walter Nicholas

• 16.1. Introduction
• 16.2. Loading Data
• 16.3. Preprocessing data
• 16.4. Select and Train a Model
• 16.5. Feature Selection and Evaluation