DEEP LEARNING (2 Credits)
Learning Outcomes:
On successful completion of this course, student will be able to:
- Explain fundamental concepts of deep learning
- Execute a proper deep learning experimentation workflow
- Analyze architecture of deep learning models
- Compose a deep learning code in Python programming
Topics:
- Introduction to Deep Learning
- Multi-layer Perceptrons
- Convolutional Neural Networks
- Recurrent Neural Networks
- Deep Neural Networks
- Practical Aspect in Deep Learning
- Deep Recurrent Neural Networks
- Deep Convolutional Neural Networks
- Attention and Memory
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