Course Outline
Introduction
Overview of Languages, Tools, and Libraries Required for Enhancing a Computer Vision Application for Government Use
Setting up OpenVINO for Government
Overview of the OpenVINO Toolkit and its Components for Government Applications
Understanding Deep Learning Acceleration with GPU and FPGA for Government Projects
Writing Software to Target FPGA in a Government Context
Converting Model Formats for an Inference Engine in Government Systems
Mapping Network Topologies onto FPGA Architecture for Government Applications
Utilizing an Acceleration Stack to Enable an FPGA Cluster for Government Use
Configuring an Application to Detect an FPGA Accelerator for Government Operations
Deploying the Application for Real-World Image Recognition in Government Settings
Troubleshooting for Government Applications
Summary and Conclusion for Government Use
Requirements
- Proficiency in Python programming
- Familiarity with pandas and scikit-learn libraries
- Experience with deep learning and computer vision techniques
Audience for government
- Data scientists working in the public sector
