- A1: Perceptron Learning with numpy
- A2: Gradient Descent with numpy
- A3: Universal Function Approximation with numpy
- A4: Multi-Output Networks and Batch Processing with numpy
- A5: Classification in Pytorch
- A6: Convolutional Networks and Comparison to FC Networks
- A7: Transfer learning
- A8: Open-Set Classification
- A9: Convolutional Auto-Encoder used for Anomaly Detection
- A10: Predict Stock Price with LSTM RNN
- A11: Adversarial Training
- A12: Zero Shot Learning and Auto Labelling Pipeline
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