100 Days of Machine Learning Code Day 1

Getting Started with #100daysofML Day 1  , in journey of learning ML/DL one encounter with images sooner or later and learning to play around with them in python is necessary , for the series of post i wil be using using a mix of google colab , Jupyter Notebook on Local Instance Github gists for code snippets and NBviewer for viewing the notebooks saved in my github repo for online view , will be skipping the basics majority of times as there are plenty of better explnation online about them and will be focsing more on the "Geeting Hands Dirty " and implementation side

Day 1 is not machine learning  and more of warm up in python that will help us later

Here is a list of  required resources in order  :
-  List of Image Manipulation Tools in Python (will be using Pillow for now)
-  Setup and Getting Started
- Adding Data in Google Colab

Prerequisites will be Python , and Running code in Jupyter Notebook, although one can easily setup and run these codes locally on your notebook but my prefernce will be to get more comfortable with Google Colab or any other cloud instance so that as one proceed you can run more GPU and CPU intensive tasks on powerful server provided you for free in learning stage rather than setting you Machine on Fire [unless you have a really good spec machine]

So the task is to get an image modify the RGB channels of the Image , in differnet intensities combine them in a 3X3 grid with image label written below each image
Here are the Links to the question statement
 - Question Statement [Week 1 Assignment of Coursera Python Pillow]
-  My Attempt at google colab

PS: I this the above link dosent work or you need individual files here is link to my #100DaysofMLcode  Github repository