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Course Outline
Introduction
Neural Networks Overview
Understanding Convolutional Networks
Setting up Keras
Overview of Keras Features and Architecture
Overview of Keras Syntax
Understanding Keras Layer Organization
Configuring the Keras Backend (TensorFlow or Theano)
Implementing Unsupervised Learning Models
Image Analysis using Convolutional Neural Networks (CNN)
Data Preprocessing
Model Training
Training on CPU vs. GPU vs. TPU
Model Evaluation
Utilizing Pre-trained Deep Learning Models
Setting up Recurrent Neural Networks (RNN)
Model Debugging
Model Saving
Model Deployment
Monitoring Keras Models with TensorBoard
Troubleshooting
Summary and Conclusion
Requirements
- Experience with Python programming.
- Familiarity with the Linux command line.
Target Audience
- Software Developers
- Data Scientists
21 Hours
