Intermediate Intel® Distribution of OpenVINO™ toolkit for Deep Learning Applications
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Course Summary
This course teaches you how to optimize deep learning models for running on CPUs and other Intel hardware using the OpenVINO toolkit.Key Learning Points
- Learn how to optimize deep learning models for Intel hardware.
- Understand the benefits of the OpenVINO toolkit.
- Develop the skills needed to deploy models to edge devices.
Related Topics for further study
Learning Outcomes
- Optimize deep learning models for Intel hardware using OpenVINO.
- Deploy optimized models to edge devices.
- Understand the benefits of using OpenVINO for deep learning optimization.
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Python and deep learning frameworks.
- Familiarity with computer vision concepts.
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video lectures
Similar Courses
- AI for Edge Computing
- Deep Learning on Edge Devices
Related Education Paths
Notable People in This Field
- Data Scientist at Intel
- Machine Learning Engineer at OpenAI
Related Books
Description
This course is designed for application developers who wants to deploy computer vision inference workloads using the Intel® Distribution of OpenVINOTM toolkit. The course looks at computer vision neural network models from a variety of popular machine learning frameworks and covers writing a portable application capable of deploying inference on a range of compute devices.
Knowledge
- How to use the Model Optimizer to convert models from popular machine learning frameworks.
- How to run benchmarks and do device comparison and validation.
- How to use the Inference Engine to deploy to multiple types of devices.
- How to use the Inference Engine’s asynchronous inference to handle various deployment situations.
Outline
- Intermediate Intel® Distribution of OpenVINO™ toolkit for Deep Learning Applications
- Introducing Intel® Distribution of OpenVINO™
- Workflow of Intel® Distribution of OpenVINO™ Toolkit Usages
- Model Optimizer
- Model Optimizer Troubleshooting
- Inference Engine: Setting Up
- Inference Engine: Running Inference
- Deployment and Intel® Hardware Selection
- Using Multiple Devices
- Benchmarking
- Optimization
- Implementation Examples: Batch of Images
- Implementation Examples: Stream of Images
- Welcome
- Course 1 Quiz
- Course 2 Quiz
Summary of User Reviews
Discover the OpenVINO toolkit and learn how to optimize your deep learning models for Intel hardware. This course has received high ratings from users and is praised for its comprehensive content and practical exercises.Key Aspect Users Liked About This Course
Many users appreciate the practical exercises that allow them to apply what they have learned in real-world scenarios.Pros from User Reviews
- Comprehensive content that covers all aspects of the OpenVINO toolkit
- Practical exercises that allow users to apply what they have learned
- Clear and concise explanations of complex topics
- Excellent support from the course instructors
- Flexible schedule that allows users to learn at their own pace
Cons from User Reviews
- Some users found the course to be too technical and challenging for beginners
- The course requires a significant time commitment to complete
- The course may not be suitable for those who are not familiar with deep learning concepts
- Some users found the course to be too focused on Intel hardware and not applicable to other platforms
- The cost of the course may be prohibitive for some users
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Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications
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Welcome to the Introduction to Intel® Distribution of OpenVINO™ toolkit for Computer Vision Applications course! Throughout this course, you will be introduced to demos, showcasing the capabilities of this toolkit....
Intermediate Intel® Distribution of OpenVINO™ toolkit for Deep Learning Applications
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This course is designed for application developers who wants to deploy computer vision inference workloads using the Intel® Distribution of OpenVINOTM toolkit....
