This course provides an introduction to deep learning on modern Intel® architecture. Deep learning has gained significant attention in the industry by achieving state of the art results in computer vision and natural language processing.
By the end of this course, students will have a firm understanding of:
- Techniques, terminology, and mathematics of deep learning
- Fundamental neural network architectures, feedforward networks, convolutional networks, and recurrent networks
- How to appropriately build and train these models
- Various deep learning applications
- How to use pre-trained models for best results
The course is structured around 12 weeks of lectures and exercises. Each week requires three hours to complete.