Hi, here are some of the resources that I prepared. I hope they are useful to you.
This document provids the fundemental of machine leaning. You can also find how to implement simple algorithms like Linear Regressoion and Logistic Regression. I have attempted to derive the gradients to implement gradient descent for these tow algorithms. I hope people who are new to ML find this useful.
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 into detailed explanation to every steps. The back propagation algorithm, a variation of which is currently used for many state of art models, is also explained with a simple example. This will be useful for people who have just started with DL.
This document contains some basic intoduction 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.
It is always irritaing to execute the same set of commands to make a commit in the remote repository. And more over you have provide username and password for every push you make. Guess what! you don’t need to do that any more. This document will guide you to set up SSH key so that you don’t need to redundantly type commands. I have also provided shortcut procedures for few sets of frequently used commands in the document.