Course Outline
Introduction
Setting up a Working Environment for Government
Installing Auto-Keras
Anatomy of a Standard Machine Learning Workflow for Government
How Auto-Keras Automates the Machine Learning Workflow for Government
Searching for the Best Neural Network Architecture with NAS (Neural Architecture Search) for Government
Case Study: AutoML with Auto-Keras for Government
Downloading a Dataset for Government Use
Building a Machine Learning Model for Government Applications
Training and Testing the Model for Government Requirements
Tuning the Hyperparameters for Optimal Performance in Government Settings
Building, Training, and Testing Additional Models for Government Needs
Tweaking the Hyperparameters to Improve Accuracy for Government Projects
Configuring Auto-Keras for Deep Learning Models in Government
Troubleshooting for Government Users
Summary and Conclusion for Government Applications
Requirements
- Experience working with machine learning models for government applications.
- Familiarity with Python programming is beneficial but not required.
Audience
- Data analysts for government agencies
- Subject matter experts (domain experts) in public sector roles
- Data scientists working in governmental contexts
