A Practical Guide to Deep Learning with Keras

Implement AI with Keras for building complex Deep Learning neural networks with fewer lines of coding in Python

Created by: Packt Publishing
Tech Knowledge in Motion

What Will I Learn?

• Install and configure Keras. Study Deep Convolutional Neural Networks.
• Develop a deep learning network from scratch with Keras using Python to solve a practical problem of classifying the traffic signs on the road.
• Get introduced to Computer Vision & Deep Learning.
• Setup and develop an environment with VM or Docker. Ipython and Jupyter notebook.
• Discover activation functions, forward propagation, backward propagation.
• Tensorboard and intuitions of filters and hyper-parameters.
• Deploy and evaluate for other real-world applications. Future work and readings!
• Learn Neural network style transfer - Image style translation and generation.
• Develop Game AI - Running game agents using Deep Q network.

Requirements

• While knowledge of the Keras framework is not required, it is assumed that you’re well versed with the Machine Learning concepts and Python programming language.

Target audience

• Software Developers, Data Scientists with experience in Machine Learning or an AI Programmer with some exposure to Neural Networks: looking to achieve the power of Artificial Intelligence and want to build some broad range of skills such as image translation, autonomous driving simulation, Deep Reinforcement Learning with AI!