Learn DeepLearning from the Basic

Learn how to implement deeplearning to recognize or learn something based on your project using numpy, tensorflow, PIL or OpenCV

Usage

• linear_regretioin_and_gradient_descent.py == deeplearning to recognize O or X images
• and_gate_grad_desc.py == deeplearning based on AND Gate
• or_gate_grad_desc.py == deeplearning based on OR Gate
• gradient_descent_3D.py == learn how to use gradient descent and plot in 3D

Getting Started linear_regretioin_and_gradient_descent.py

To run linear_regretioin_and_gradient_descent.py you need picture X and O to learn and testing purposes. the input is the number of images with X and O and the result is prediction by computer using the number, when the result after training approaching 0 then the result is X otherwise, when the result after training approaching 1 then the result is O. It depends how you design your network. in my case approaching 0 is X, approaching 1 is 0.

Prerequisites

You can download the X or O images here :

• Images - The Images

How to Use

Then you need change the images directory based on where you save the images in loadImage() method