- Study and document the evolution of ANN from Perceptron with derivation.
- Document problems generally faced in training an ANN and their solution provided in the lecture with derivation.
- Compare and document different available activation functions.
- Compare and document different available weight initialization techniques.
- Observe and document results before and after applying Batch Normalisation.
- Observe and document results before and after applying Transfer Learning.
- Observe and document use of Early Stopping and Check-pointing.
- Compare and document different available Optimizers and their derivation.
- Observe and document the use of various loss functions.
- Observe and document results before and after applying various regularisation techniques like l1, l2, and dropout techniques.
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Note : Some of the notebook contain latex code which doesn not support in github. You can open the notebook in google drive.