If you’re planning to learn machine learning online for free, this post is for you.
Based on content type, I categorized the resources into three groups.
You can learn machine learning by
Watching
Online Courses
This course will give you a brief and high-level introduction to machine learning. The course is well structured as even non-technical people can understand the core concepts in machine learning and its process.
Coursera Machine Learning course - Andrew ng
This course is the mother of all machine learning courses out there online. It’s heavily focused on maths behind machine learning algorithms and building the model from scratch.
The technology used in this course is octal.
As per my research, this octal language is deprecated from the industry now.
But you can still grasp the nuts and bolts behind machine learning algorithms from this course.
Introduction to Machine Learning - MIT open learning library
This course introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction.
Introduction to Machine Learning - udacity
This course will provide the machine learning foundations with some commonly used machine learning algorithms.
Machine Learning Crash Course - Google
This has been the internal course for google developers in the past. It’s now publicly available for all.
This course heavily focuses on the TensorFlow library, which world most used python library out there.
Machine Learning with Python: A Practical Introduction - edx.org
One of the free courses to learn machine learning on the edx site.
Youtube
Making Friends with Machine Learning- Google
The playlist name itself is self-descriptive about this youtube playlist.
Machine learning with Python - Codebasics
This playlist is well-structured and easy to understand for beginners.
Machine Learning - StatQuest with Josh Starmer
In this playlist, the author will guide you to learn machine learning with fun-filled content.
Reading
Books
This webbook is more focused on deep learning. But the initial chapters will give a solid understanding of core machine learning concepts.
Also, it’s well documented the maths behind machine learning algorithms.
Python Data Science Handbook - _Jake VanderPlas, Oreilly
This webbook provides hands-on experience with essential machine learning tools like NumPy, pandas, and matplotlib.
Blogs and Websites
It’s a step-by-step machine learning tutorial site.
Kagges is a defacto site for machine learning competitions and open datasets.
They are providing free resources to learn Machine Learning fundamentals.
Machine Learning with Python - freecodecamp.org
Hands-on machine learning tutorial by famous content creator Tim.
Machine Learning - w3schools.com
If you’re from a programming background you are familiar with w3school. It is one of the world’s largest web developer site.
In the machine learning section on the python reference page, beginners can refer to introductory content for machine learning.
This blog is focused on machine learning content with practical real-world applications with python libraries.
Github Repos
These are some of the GitHub repositories has rich machine learning resources within.
Awesome Machine Learning On Source Code
Doing
Introduction to Machine Learning for Coders - fast.ai
In-depth machine learning real-world application tutorial by Jeremy Howard.
This course is updated its content on regular basics and please take an eye on this site as well.
Scikit-learn - Learning resource
Scikit-learn is open source, commercially usable library for machine learning.
Bonus tip
Try to learn machine learning through your native language.
At first, it feels awkward to hear machine learning word itself in your native language. But it will give you a different perspective on the subject.
Do some research for machine learning study materials in your native language.
(Spoiler - ML is a hot topic nowadays, so chances of getting valuable Machine Learning resources in your native language are high).
Summary
I summarized free machine learning study materials online based on the learning type (watching, reading, and doing,).
The resources are based on my preference.
Go through with these resources. Based on your learning style, pick one of the materials and get started with machine learning.
Happy learning/coding!