Resources

Hi, here are some of the resources that I authored. I hope they are useful to you.

Machine Learning

This document provides the fundamental understanding of machine leaning. You can also find how to implement simple algorithms like Linear Regression and Logistic Regression. I have attempted to derive the gradients to implement gradient descent for these two algorithms. I hope people who are new to ML find this useful.

Deep Learning

This document explains the mathematical modeling of Artificial Neural Network, with explanations to general notations used in various research works. I have attempted to break down the math with detailed explanation to every steps. The vanilla back propagation algorithm, a variation of which is currently used for many state of art models, is also explained with a simple example. I hope this will be useful for people who have just started with DL.

Image Processing

This document contains a basic introduction to image processing and will guide you to do a complete installation of anaconda software along with all libraries needed to do Image Processing and Deep Learing in python. I have also uploaded few sample code in this repository.