An application to recognise the cat images with the Accuracy of 80 %. From this project, I've learn how to: Build the general architecture of a learning algorithm, including: Initializing parameters Calculating the cost function and its gradient Using an optimization algorithm (gradient descent) Gather all three functions above into a main model…

Generic L-layer 'straight in Python' fully connected Neural Network implementation using numpy.

L layer deep neural network for image classification.

Implemented an L-layer neural network to classify images as being of a cat or not from scratch without using any deep learning libraries like TensorFlow or PyTorch

Its somewhat general way to create a N Layer Tensorflow Neural Network but here I used a Mnist Dataset