Course Outline
Introduction
Overview the Languages, Tools, and Libraries Needed for Accelerating a Computer Vision Application
Setting up OpenVINO
Overview of OpenVINO Toolkit and its Components
Understanding Deep Learning Acceleration GPU and FPGA
Writing Software That Targets FPGA
Converting a Model Format for an Inference Engine
Mapping Network Topologies onto FPGA Architecture
Using an Acceleration Stack to Enable an FPGA Cluster
Setting up an Application to Discover an FPGA Accelerator
Deploying the Application for Real World Image Recognition
Troubleshooting
Summary and Conclusion
Requirements
- Python programming experience
- Experience with pandas and scikit-learn
- Experience with deep learning and computer vision
Audience
- Data scientists
Delivery Options
Private Group Training
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- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from £9500 online delivery, based on a group of 2 delegates, £3000 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses