This guide is intended for anyone having zero or a small background in programming, maths, and machine learning. There is no specific order to follow, but a classic path would be from top to bottom. If you don't like reading books, skip it, if you don't want to follow an online course, you can skip it as well. There is not a single way to become a machine learning expert and with motivation, you can absolutely achieve it.

All resources listed here are free, except some online courses which are certainly recommended for a better understanding, but it can certainly be done without it with a little more reading and practice.

Don't be afraid to repeat videos or learn from multiple sources. Repetition is the key of success to learning!

Maintainer - louisfb01

Feel free to message me any great resources to add to this repository on [email protected]

Tag me on Twitter @Whats_AI or LinkedIn @Louis (What's AI) Bouchard if you share the list!

• Start with short YouTube video introductions
• Follow free online courses on YouTube
• Read articles
• Read books
• No coding background, no problem
• Follow online courses
• Practice, practice, and practice!
• More Resources (Communities, cheat sheets, news, and more!)

This is the best way to start from nothing in my opinion. Here, I list a few of the best videos I found that will give you a great first introduction of the terms you need to know to get started in the field.

• Introduction to the most used terms

  • Learn the basics in a minute - What's AI - YouTube Playlist

• Understand the neural networks

  • Neural Networks Demystified - Welch Labs - YouTube Playlist
  • Learn Neural Networks - 3Blue1Brown - YouTube Playlist

Here is a list of awesome courses available on YouTube that you should definitely follow and are 100% free.

• Introduction to machine learning - YouTube Playlist (Stanford)

• Introduction to deep learning - YouTube Playlist (MIT)

• Deep learning specialization - YouTube Playlist (Deeplearning.ai)

• Deep Learning (with PyTorch) - YouTube Playlist (Yann LeCun)

Here is a list of awesome articles available online that you should definitely read and are 100% free.

• Start Machine Learning in 2021 - Become an expert for free! - Louis Bouchard
• 5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python - Daniel Bourke
• What is Machine Learning? - Roberto Iriondo
• Machine Learning for Beginners: An Introduction to Neural Networks - Victor Zhou
• A Beginners Guide to Neural Networks - Thomas Davis
• Understanding Neural Networks - Prince Canuma
• Reading lists for new MILA students - Anonymous
• The 80/20 AI Reading List - Vishal Maini

Here are some great books to read for the people preferring the reading path.

• Deep learning book - Free Online
• Dive into Deep Learning - Free Online
• Mathematics for Machine Learning - Free Online
• Artificial Intelligence: A Modern Approach - Optional (Paying)
• Pattern Recognition and Machine Learning - Optional (Paying)
• The Elements of Statistical Learning - Optional (Paying)
• Deep Learning with Python - Optional (Paying)

Here is a list of some great courses to learn the programming side of machine learning.

• Learn Python - Free interactive tutorial to learn python
• Learn Python Basics for Data Analysis - Free course on OpenClassrooms
• Machine Learning with Python | Coursera - IBM - Optional (Paying)

If you prefer to be more guided and have clear steps to follow, these courses are the best ones to do.

• DEEP LEARNING - Yann LeCun - This course concerns the latest techniques in deep learning and representation learning. - Free
• Intro to Machine Learning - Kaggle - Learn the core ideas in machine learning, and build your first models. - Free
• Get started in AI / AI For everyone - Andrew Ng
• Machine learning - Andrew Ng - Stanford
• Deep learning specialization - Andrew Ng
• TensorFlow (Professional certificates)
• AI Engineering - IBM (Professional certificates)
• Complete data science bootcamp 2020
• Machine learning - No coding
• fast.ai's Deep Learning Courses - Free

The most important thing in programming is practice. And this applies to machine learning too. It can be hard to find a personal project to practice.

Fortunately, Kaggle exists. This website is full of free courses, tutorials and competitions. You can join competitions for free and just download their data, read about their problem and start coding and testing right away! You can even earn money from winning competitions and it is a great thing to have on your resume. This may be the best way to get experience while learning a lot and even earn money!

You can also create teams for kaggle competition and learn with people! I suggest you join a community to find a team and learn with others, it is always better than alone. Check out the next section for that.

• A Discord server with many AI enthusiasts - Learn together, ask questions, find kaggle teammates, share your projects, and more.

• Follow reddit communities - Ask questions, share your projects, follow news, and more.

  • artificial - Artificial Intelligence
  • MachineLearning - Machine Learning (Biggest subreddit of the field)
  • DeepLearningPapers - Deep Learning Papers
  • ComputerVision - Extracting useful information from images and videos
  • learnmachinelearning - Learn Machine Learning
  • ArtificialInteligence - AI
  • LatsestInML - Game-changing developments in machine learning you shouldn't miss

• The best Cheat Sheets for Artificial Intelligence, Machine Learning, and Python.
  • Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data - Stefan Kojouharov
  • Machine Learning cheatsheets for Stanford's CS 229 - Afshine Amidi & Shervine Amidi
  • Cheat Sheet of Machine Learning and Python (and Math) Cheat Sheets - Robbie Allen

• Subscribe to YouTube accounts that share new papers - Stay up to date with the news in the field!

  • What's AI - Weekly videos covering new papers
  • Two Minutes Papers - Bi-weekly videos covering new papers

• LinkedIn Groups

  • Artificial Intelligence, Machine Learning and Deep Learning News - News of the field shared by everyone in the group
  • Artificial Intelligence | Deep Learning | Machine Learning
  • Applied Artificial Intelligence

• Follow Medium accounts and publications

  • Towards Data Science - "Sharing concepts, ideas, and codes"
  • Towards AI - "The Best of Tech, Science, and Engineering."
  • OneZero - "The undercurrents of the future. A Medium publication about tech and science."
  • What's AI - "Hi, I am Louis (loo·ee, French pronunciation), from Montreal, Canada, also known as "What's AI". I try to share and explain artificial intelligence terms and news the best way I can for everyone. My goal is to demystify the AI “black box” for everyone and sensitize people about the risks of using it."

Tag me on Twitter @Whats_AI or LinkedIn @Louis (What's AI) Bouchard if you share the list!