From the course: Self-Supervised Machine Learning
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Summary and next steps
From the course: Self-Supervised Machine Learning
Summary and next steps
- [Instructor] And this demo brings us to the very end of this course on self-supervised machine learning. Let's take a look at the references, summary, and next steps. Here are some references that I used while drawing up the material for this course. If you're interested in studying this topic further, these references form an amazing source. I highly recommend this YouTube video that you see here by Ishan Misra. He's one of the original authors of the SwAV paper. Here's what we've covered in this course. We started off by discussing what exactly self-supervised learning was and why it's needed. We then defined pretext tasks and downstream tasks, and we saw that self-supervised learning techniques are usually used in pretext tasks. We then focused our attention to the field of computer vision, and we saw how we could set up pretext tasks using images, video, and video and sound. We then discussed self-supervised…
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