Create and visualize your very first Neural Network in Python

[For Absolute Beginners] If you are new to neural networks and always wanted to create your first neural network but could not get yourself started, this tutorial is exactly for you.

This tutorial is totally created for absolute beginners who want to create their very first neural network without consideration of math, or stats, or any machine learning knowledge. 

In this tutorial, we will be using both Keras and TensorFlow as the foundation for our deep learning framework and utilize the power of Keras and TensorFlow to write the neural network from scratch by defining the input, output and the layers in-between.  There are various other concepts discussed and created using the network visualization method to make the learning easier and effective. Neural Network visualization along with source code, is used side by side to make sure each line in the code is understood properly. 

At last we have used a pre-trained network for prediction and visualized its layers to understand what a full working neural network looks like after it is ready, to provide the actual scope of learning to the students. 

The content timeline is as below:
- (00:00) Tutorial Starts
- (00:40) Content Intro
- (04:41) Getting started
- (12:18) Helpful Reference 
- (13:04) Neural Network Visualization
- (25:15) Creating sequential neural network 
- (35:51) Neural Network Parameters and Feed Forward Network
- (52:35) Pre-trained Network (full example)
- (01:05:55) Fully Connected Layers
- (01:09:45) Recap
- (01:11:22) Tutorial Source Code 

Jupyter notebook Source code:

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