Course Outline

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

Requirements

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

Audience

  • Developers
  • Data scientists
  21 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 09:30 and 16:30.
Open Training Courses require 5+ participants.

Testimonials (3)

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