5 Free YouTube Channels Dedicated to Machine Learning Education

Well, you can always choose a self-paced online course that best aligns with your learning preferences. But if you prefer learning from some of the best educators and experienced professionals—all for free—then YouTube is a great learning resource.

This is a list of YouTube channels that have high-quality content on machine learning, taught by great instructors, and loved by millions of learners across the world. So let’s go over these YouTube channels.

1. StatQuest with Josh Starmer

If you’re a beginner in machine learning, StatQuest with Josh Starmer is a great place to start. Josh Starmer is an excellent educator who makes statistics and machine learning super accessible.

Machine learning algorithms can feel intimidating but Josh Starmer breaks down how they work into easy-to-follow tutorials. The channel has in-depth content on the following machine learning topics:

• Linear regression and linear models
• Logistic regression
• Decision trees and random forests
• Support vector machines
• XGBoost

After you’re comfortable with machine learning, you can as well explore the deep learning tutorials on this channel.

2. Codebasics

Codebasics is a popular YouTube channel run by Dhaval Patel. You can learn programming, data analysis, and machine learning on this channel.

This channel has super helpful content on the following:

• Python programming
• Math and stats for data science machine learning
• Machine learning projects on real-world datasets

Besides foundational machine learning concepts, you can also explore tutorials on natural language processing, building applications with large language models, and more.

3. freeCodeCamp

If you work in tech, you’re probably already familiar with freeCodeCamp and their mission to make learning to code and learn all things tech super accessible. The freeCodeCamp community YouTube channel is a repository of high-quality video courses and tutorials  to learn programming, data science, and software development.

The Machine Learning playlist has several full-length video courses on the following:

• Machine learning for beginners
• Machine learning from scratch—without using libraries
• Building machine learning models with scikit-learn
• Building neural networks with PyTorch, TensorFlow, and Keras
• Computer Vision in Python

You can also find in-depth tutorials to learn the prerequisites—Python and data analysis with pandas—before you get into machine learning. The channel also has interview preparation courses to help you ace technical and coding interviews.

4. Sentdex

Sentdex is another excellent YouTube channel to learn Python programming, machine learning, and deep learning.

The Machine Learning with Python playlist has practical and in-depth tutorials covering:

• Building regression models
• Evaluating regression models
• K Nearest Neighbors and Support Vector Machines
• Clustering algorithms
• Deep learning fundamentals

Besides machine learning, this channel also has a ton of useful Python tutorials on GUI development, data analysis, image and video analysis with OpenCV, and more.

5. Data School

Data School is another YouTube channel by Kevin Markham that has helpful content to learn data science. This channel offers easy-to-follow tutorials on Python, data analysis, and machine learning with scikit-learn.

Before you get into machine learning, you should be comfortable with Python programming and data analysis. Particularly, you should be able to:

• Scrape the web programmatically using Python to get the data
• Clean and analyze the dataset
• Build machine learning models with the scikit-learn library

AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI
With Data School, you can learn all of this and much more. In addition, the scikit-learn tips playlist has helpful nuggets to help you follow the best practices when building machine learning models with scikit-learn.

Wrapping Up

And that’s a wrap. As mentioned, YouTube is an excellent learning resource to learn machine learning (and almost any technical topic). But there’s the caveat of passively consuming content—watching one tutorial after another—without learning effectively.

It is only when you do things you actually learn and understand. So when you’re working through video tutorials, remember to set up the dev environment and code along. From setting up the environment and installing the required libraries to tuning hyperparameters, it’s only when you get your hands dirty that you actually learn. Happy learning and coding!