Practical Deep Learning: A Python-Based Introduction Book by Ronald T. Kneusel

All you need is basic familiarity with computer programming and high school math—the book will cover the rest. After an introduction to Python, you’ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance.

You’ll also learn:
How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines
How neural networks work and how they’re trained
How to use convolutional neural networks
How to develop a successful deep learning model from scratch

You’ll conduct experiments along the way, building to a final case study that incorporates everything you’ve learned.

The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects.