Implementation of Deep neural network from scratch. Following the course by DeepLearning.ai and NNFS here is the implmentation for building your own Neural Network using Vanilla Python.
Resources for understanding concepts in DNN
https://docs.google.com/document/d/1lM-hM5fFjPF2nZFn4iVkrCymGNPgklHgyXt1vvfqlLo/edit?usp=sharing
Features yet to be implemented.
- Generalised load_dataset Function
- Weights Initialization
- Normalizing Input
- L2 Cost Regularisation (Done)
- Droput Method (Need to add test cases)
- Other Regularisation
- Gradient Check
- Mini Batch (Done)
- Exponentially Weighted Average
- Bias Correction in Exponentially Weighted Average
- RMSprop
- Gradient Descent with Momentum (Done)
- Adam Optimiser
- Learning Rate Decay
- Other Activation Function Support