Neural-Network-Library-From-Scratch

Note: This is not intended for professional use for obvious reasons and is just a fun personal project.
Also, do have a look at mnist-example.ipynb to see how to use it. Although, it's pretty intuitive and is quite similar to the beginner-friendly Keras's API

Supported Activation functions

• Sigmoid
• ReLu
• Tanh

Under progress

• Softmax

Supported Loss functions

• Mean Squared Error

Under progress

• Binary Cross Entropy