My latest YouTube video is 25 hours, 36 minutes and 57 seconds long (actually a little over a day).
And its sole purpose is to be a momentum builder, to help you learn PyTorch for deep learning.
The video is comprised of 162 smaller videos, or the first five chapters of the Zero to Mastery PyTorch for deep learning course:
- 00 - PyTorch and deep learning fundamentals
- 01 - PyTorch workflow
- 02 - PyTorch neural network classification
- 03 - PyTorch computer vision
- 04 - PyTorch custom datasets
In each section, we'll get hands-on and learn important machine learning concepts by writing PyTorch code together, apprenticeship style.
It still amazes me to think how much the field of machine learning is progressing.
There are things in the video that weren't possible 10 years ago.
Now they are with a few lines of PyTorch code and free tools like Google Colab (what we'll use throughout the video).
If you've got a few months of Python coding experience and would like to get into the world of machine learning and become familiar with PyTorch, the video is for you.
And if you finish the video and find yourself wanting more, you can find another five chapters of PyTorch code at learnpytorch.io:
- 05 - PyTorch going modular
- 06 - PyTorch transfer learning
- 07 - PyTorch experiment tracking
- 08 - PyTorch paper replicating
- 09 - PyTorch model deployment (coming soon)
The videos (20+ more hours) for the later sections are available in the Zero to Mastery Learn PyTorch for Deep Learning course.
To read more about the full course, see the launch blog post.