Course Outline
Introduction
Overview of Neural Networks for Government
Understanding Convolutional Networks in Public Sector Applications
Setting up Keras for Government Use
Overview of Keras Features and Architecture for Government Projects
Overview of Keras Syntax for Government Developers
Understanding How a Keras Model Organizes Layers for Government Applications
Configuring the Keras Backend (TensorFlow or Theano) for Government Systems
Implementing an Unsupervised Learning Model for Government Data Analysis
Analyzing Images with a Convolutional Neural Network (CNN) in Government Contexts
Preprocessing Data for Government Models
Training the Model for Government Applications
Training on CPU vs GPU vs TPU for Government Efficiency
Evaluating the Model for Government Performance Standards
Using a Pre-trained Deep Learning Model in Government Projects
Setting up a Recurrent Neural Network (RNN) for Government Use
Debugging the Model for Government Accuracy
Saving the Model for Government Record-Keeping
Deploying the Model in Government Operations
Monitoring a Keras Model with TensorBoard for Government Oversight
Troubleshooting Common Issues for Government Users
Summary and Conclusion for Government Stakeholders
Requirements
- Python programming experience.
- Experience with the Linux command line.
Audience
- Developers for government
- Data scientists
