Atheb
Joined 9 years ago
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Member since
Jun 14
Joined 9 years ago
Because I am still in the academic process, I had the opportunity to take a couple of classes on the subject. Three books that I would recommend going over to make sure your foundation in ML and mathematics are solid are
-Pattern recognition and machine learning by Christopher Bishop
-Mathematics for Machine Learning by Peter Deisenroth
-Deep Learning by Courville, Bengio and Goodfellow
All three are legally available online in some form. I can't say I have any experience in finding a job related to ML though.
I mostly work when it feels right, yes, and do something else when it doesn't. But I am doing my PhD and (in Canada) it absolutely does not pay enough to live comfortably.
There is a lot of overlap here with the authoring process of a Word document. You don’t necessarily want the real-time coauthoring experience offered by Microsoft SharePoint or Google Docs., this can inhibit your ability to determine who is responsible for specific changes to content. Branching offers a much clearer audit trail of changes. Like with code, tags can be added to signify a minor or major version of a document is ready to be published.
While it's very cool, I'm shivering at the idea of teaching Git to non-technical people. And it still seems like a non-realtime version of Google Docs because Gdocs does offer audits
Justin Johnson's lecture on Attention [1] mechanisms really helped me understand the concept of attention in transformers. In the lecture he goes through the history and and iterations of attention mechanisms, from CNNs and RNNs to Transformers, while keeping the notation coherent and you get to see how and when in the literature the QKV matrices appear. It's an hour long but it's IMO a must watch for anyone interested in the topic.
[1]: https://www.youtube.com/watch?v=YAgjfMR9R_M