Deep Learning For Dummies - code repository maintained by one of the authors

Note: code in most examples has been updated to run with the most recent version of TensorFlow

Authors: John Paul Mueller, Luca Massaron

Deep learning provides the means for discerning patterns in the data that drive online business, medicine, research, social media outlets, and many elements of daily life. This book gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with it. In no time, you’ll make sense of those increasingly confusing algorithms, and find a simple and safe environment to experiment with deep learning.

You can run all the examples in the book on Google Colab by simply using the links below:

• Chapter 3 - Comments

• Chapter 3 - Dataset Load

• Chapter 3 - Indentation

• Chapter 3 - Sample

• Chapter 5 - Reviewing Matrix Math and Optimization

• Chapter 6 - Laying Linear Regression Foundations

• Chapter 8 - Neural Networks from Scratch

• Chapter 10 - LeNet

• Chapter 12 - German Traffic Sign Benchmark

• Chapter 12 - Object Detection with Keras RetinaNet

• Chapter 14 - Movie Sentiment

• Chapter 14 - Processing Language

• Chapter 16 - MNIST GAN

• Chapter 17 - Reinforcement Learning