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Learn how to setup and use VSCode as an IDE on Google Colab and Kaggle. I recently discovered a way to set up VSCode on Google Colab and use it as an editor to write code and run experiments on the Colab VM. With this setup, you can still prototype in the Colab Notebook while also using VSCode for all the advantages of a full-fledged code editor. Here is how you can replicate my setup. Approach 1:
I recently came across an interesting thread on Twitter discussing a hypothetical scenario where research papers are published on GitHub and subsequent papers are diffs over the original paper. Information overload has been a real problem in ML with so many new papers coming every month. If you could represent a paper as a code diff, many papers could be compressed down to <50 lines :) The diff wo
An overview of self-supervised pretext tasks in Natural Language Processing While Computer Vision is making amazing progress on self-supervised learning only in the last few years, self-supervised learning has been a first-class citizen in NLP research for quite a while. Language Models have existed since the 90’s even before the phrase “self-supervised learning” was termed. The Word2Vec paper fro
Unlike Computer Vision where using image data augmentation is standard practice, augmentation of text data in NLP is pretty rare. Trivial operations for images such as rotating an image a few degrees or converting it into grayscale doesn’t change its semantics. This presence of semantically invariant transformation made augmentation an essential toolkit in Computer Vision research. I was curious i
A visual introduction to self-supervised learning methods for visual representations. I first got introduced to self-supervised learning in a talk by Yann Lecun, where he introduced the “cake analogy” to illustrate the importance of self-supervised learning. In the talk, he said: “If intelligence is a cake, the bulk of the cake is self-supervised learning, the icing on the cake is supervised learn
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