Deep Learning with Keras

• Python Programming experience.
• Experience with the Linux command line.

Audience

• Developers
• Data scientists

Keras is a high-level neural networks API for fast development and experimentation. It runs on top of TensorFlow, CNTK, or Theano.

This instructor-led, live training (online or onsite) is aimed at technical persons who wish to apply deep learning model to image recognition applications.

By the end of this training, participants will be able to:

• Install and configure Keras.
• Quickly prototype deep learning models.
• Implement a convolutional network.
• Implement a recurrent network.
• Execute a deep learning model on both a CPU and GPU.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about Keras, please visit: https://keras.io/

Introduction

Overview of Neural Networks

Understanding Convolutional Networks

Setting up Keras

Overview of Keras Features and Architecture

Overview of Keras Syntax

Understanding How a Keras Model Organize Layers

Configuring the Keras Backend (TensorFlow or Theano)

Implementing an Unsupervised Learning Model

Analyzing Images with a Convolutional Neural Network (CNN)

Preprocessing Data

Training the Model

Training on CPU vs GPU vs TPU

Evaluating the Model

Using a Pre-trained Deep Learning Model

Setting up a Recurrent Neural Network (RNN)

Debugging the Model

Saving the Model

Deploying the Model

Monitoring a Keras Model with TensorBoard

Troubleshooting

Summary and Conclusion