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