Implementing_

Here's were I try and build some cool stuff from scratch inorder to better understand them.

1.Build a neural net from scratch only NumPy

Dependencies to run this code :

• Numpy(numerical computational library)
• sklearn(for a dataset to train and test the network)

If you dont have the dependencies installed type the following in your command line:

• $pip3 install numpy
• $pip3 install sklearn

Link to code below.

NN_from_Scratch.py

2.A Neural Algorithm of Artistic Style- Leon A. Gatys,Alexander S. Ecker,Matthias Bethge

https://arxiv.org/abs/1508.06576
Learnt a lot along the way.From Tensorflow Eager Execution to Gram Matrix.
I've tried my best to document and comment each step along the way.
You can run this directly on Google colab ,link

here In this case I suggest to work on google colab with a GPU runtime as we get both the hardware and there is no hassle to setup the dependencies.

Here are some sample results(This is not the best implementation):