A Practical Guide to Deep Learning with Keras

Keras is an Open source Neural Network library written in Python. It is a Deep Learning library for fast, efficient training of Deep Learning models. It is a minimal, highly modular framework that runs on both CPUs and GPUs and allows you to put your ideas into action in the shortest possible time. Because it is lightweight and very easy to use, Keras has gained quite a lot of popularity in a very short time.

This comprehensive 3–in–1 course takes a step–by–step practical approach to implement fast and efficient Deep Learning models: Projects on Image Processing and Reinforcement Learning. Initially, you’ll learn backpropagation, install and configure Keras to understand callbacks and customize the process. You’ll develop a deep learning network from scratch with Keras using Python to solve a practical problem of classifying the traffic signs on the road. Finally, you’ll get to grips with Keras to implement fast and efficient deep–learning models with ease.

Towards the end of this course, you’ll use AI with Keras for building complex Deep Learning networks with fewer lines of coding in Python.

Contents and Overview

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Deep Learning with Keras, covers implementing deep learning neural networks with Python. Keras is a high–level neural network library written in Python and runs on top of either Theano or TensorFlow. It is a minimal, highly modular framework that runs on both CPUs and GPUs and allows you to put your ideas into action in the shortest possible time. This course will help you get started with the basics of Keras, in a highly practical manner.