Machine learning has revolutionized the world in a very short span of time. Since the data is growing on the exponential rate we need to learn how to process it and gain insights from it.
Machine learning is a field that combines stats and software development into one profession whose primary goal is to build predictive models.
In order to stay top of the field, we need to constantly learn new things. One of my favorite ways is to learn from smarter people and, if possible, do that for free.
In this article, we will go through the top 7 YouTube channels for you to harness yourself with the knowledge of machine learning.
If you are someone who likes to understand everything from scratch then this is by the far the best YouTube channel to learn about Machine Learning.
If you are keen to learn every algorithm’s workflow like how does bias and intercept get updated at every epoch, or how to implement a given machine learning algorithm from scratch then you must check the following series made by Harrison Kinsley himself.
2. Data School
Kevin Markham who is the founder of dataschool.io and the owner of the YouTube channel Data School educates machine learning enthusiasts. You can get a comprehensive understanding of machine learning regardless of your educational background thanks to Kevin‘s teaching.
Kevin also makes videos that cover several tools like pandas, NumPy, scikit-learn that will help you build your machine learning models.
You can binge-watch the following series created by Kevin to get a good grasp of the machine learning fundamentals.
Channel: Data School
3. Artificial Intelligence – All in One
The courses on Artificial Intelligence – All in One covers topics like text mining, text retrieval, and search engines, Neural Networks, and Computer Vision.
You may want to check out the following series to get an excellent grasp over machine learning concepts which is taught by Andrew Ng himself.
“Deep Learning is a superpower. With it, you can make a computer see, synthesize novel art, translate languages, render a medical diagnosis, or build pieces of a car that can drive itself. If that isn’t a superpower, I don’t know what is.” – Andrew Ng
If you want to dive deep into deep learning then you should check out the following series.
5. Machine Learning with Phil
Source: Phil Tabor
Phil Tabor is a machine learning engineer who creates educational videos in the domain of machine learning and deep learning.
He has created a great playlist regarding Deep Reinforcement Learning tutorials where he is teaching the core concepts of reinforcement learning like deep deterministic policy gradients in TensorFlow 2, Soft actor-critic in PyTorch, Robotic Control with TD3, and many more.
Channel: Machine Learning with Phil
6. Jeremy Howard
Jeremy Howard is a data scientist who has an educational background in philosophy but later out of the curiosity he harnessed himself with the knowledge of stats and programming to build the most effective and easy-to-use library for deep learning tasks fastai.
Making deep learning models was never that easy before fast.ai came into the picture. If you are someone who wants to build deep learning models that complete the task in the field of computer vision like image segmentation, image classification, image restoration with the minimal coding, and maximum results then the fast.ai is suitable for you.
You might wanna binge watch the following series to get a good grasp of deep learning with the help of the fast.ai library.
Channel: Jeremy Howard
7.Two Minute Papers
Source: Two Minute Papers
Two Minute Papers is an awesome channel for anyone who loves to be updated with the latest research going on in the Machine Learning domain.
Two Minute Papers make 2 minutes (almost) long videos explaining a research paper.
If you are keen into research field then you may want to check out the following series
Channel: Two Minute Papers
We have listed out the best channels to learn machine learning for free, but you have to be adamant to learn it and you can only learn machine learning by putting your knowledge into practice.
Best of luck on your machine learning journey. 🙂