Introduction to Neural Networks (Create a neural network using Numpy)
In this assignment, you will build a complete neural network using Numpy. You will implement all the steps required to build a network - feedforward, loss computation, backpropagation, weight updates etc.
You will use the MNIST dataset to train your model to classify handwritten digits between 0-9.
The assignment is divided into the following sections:
- Data preparation
- Feedforward
- Loss computation
- Backpropagation
- Parameter updates
- Model training and predictions
For Ipython notebook: (Refer to Neural-Networks-using-Numpy.ipynb file)
For the dataset: (Refer to mnist.pkl.gz file)
If you are unable to view or load the jupyter IPython notebook via Github, please click on this link. Thank you!