This repository contains resources, projects and anything else people have created during the 30 Days of Machine Learning Challenge.
The 30 Days of ML Challenge is a challenge where you can learn anything you want that will connect with machine learning, help resolve each other's doubt, learn with the community and share your daily learnings with each other.
In this challenge, people will post daily updates about whatever they've learned, be it any videos lectures, blog, project or anything else.
To begin the challenge, you need to join our Discord and post your daily learnings. You should also tell us your projects or works you've created under the challenge by adding their links below.
Here is a sample of what the message may look like in our Discord server -
Day 1, Started with Introduction to ML course by Andrew Ng, learned about linear regression in lecture 1
This is just a template and there won't be any limitation of format or anything. This is how we can daily share our learnings so that we can stay motivated as well as we can post our doubts and work on them together.
These are the comprehensive names of those who took the challenge with their repository and their works:
- Ankur Gupta : Github Repository
- Harsh Vishwakarma : Github Repository
- Rajat Bhaskare : Github Repository
- Ujjwal Agrawal: Github Repository
- Sanskriti Gupta : Github Repository
These are some of the resources the community has used throughout the challenge:
- Machine Learning Playlist by Codewithharry
- Machine Learning by Andrew Ng offered by Stanford on Coursera Direct link: CS 229 Stanford
- Introduction to Machine Learning by Lawrence Carin on Coursera
- Machine Learning with Python by Saeed Aghabozorgi on EdX
- Kaggle Free ML Course with Free Certification
- JavaTPoint Tutorial Series for Machine Learning
- FreecodeCamp Data Analysis with Python
- FreecodeCamp Machine Learning with Python
- Freecodecamp Scientific Computing with Python
- Freecodecamp Roadmap for Machine Learning and Data Science
- Elements of AI
- Interview Questions
- Grokking Deep Learning(Book)
- Google's Machine Learning Course
- Fast.ai Practical Deep Learning for Coders
- Foundations and MLOps by Goku Mohandas
- Machine Learning
Feel free to add an issue or a pull request, if you're working on the challenge, you can add your names to the Links above and the resources you're using to the Resources mentioned above.