Neural Networks [Machine Learning] #4: Python Implementation

Here's the link to the GitHub repository - https://github.com/antaloaalonso/Basic-Python-Neural-Netwokrs

In this video, I explain the code behind a basic Neural Network (a machine learning model). Note that I am not using a library as the code for the Neural Network.

I begin by explaining the functions of all the lines of code. I don't aim to teach the actual python programming language in much detail, so you could say that I am just giving an overview of the code. You should still gain an understanding of what different sections of the code do.

From there I move onto comparisons of NN using and not using things such as biases, and derivatives (yes, you can have a Neural Network without these things, although as you will see, they don't perform nearly as well).

Additionally, I explain what overfitting is and how it must be considered in making an ML model. I also briefly cover underfitting, however, the primary focus is on overfitting.

Here's the link to the first video - https://www.youtube.com/watch?v=SjfZhjWMiwo ... https://www.youtube.com/watch?v=fgxD9GuEP74