| Topic 01 |
Introduction to Deep Learning |
Elements of Neural Networks |
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| Topic 02 |
Optimization in Deep Neural Networks |
Training NNs, Gradient Descent Algorithm, Mini-batch gradient descent, Gradient Descent with Momentum, Learning Rate Scheduling, Batch Normalization |
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| Topic 03 |
Generalization and Regularization Techniques in Deep Neural Networks |
Bias-Variance Trade off, Weight Decay, Dropout, Data Augmentation, Early Stopping |
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| Topic 04 |
Convolutional Neural Network (CNN) |
Convolutions for feature extraction, Pooling, CNN architecture design |
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| Topic 05 |
RNN, LSTM |
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| Topic 06 |
Transformers |
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