What are the best ways to learn about deep learning?

Submitted by Tureep t3_10k2cnt in deeplearning

Starting a group project in college about "Brain tumor segmentation using deep learning" and searching for a summer internship in the subject. I usually approach a new area by looking at youtube videos, looking at some slides from teachers, and perhaps testing simpler code examples. We were now told to research the field for two weeks prior to starting and hence I'm searching for recommendations to effectively learn to be able to contribute to the project.

Looking for any tips like websites (just found Kaggle for an example), threads, code, channels, methods, topics to focus/prioritize, frameworks to prefer/avoid, articles, books etc.

Skills: Intermediate Python/c++, 3rd year MSc, little-to-no knowledge about machine learning.

Resources: Slides, An "expert" (PhD from college), eight group members, RTX 3060 Ti (and Azure hours later).

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SimulatedAnnealing t1_j5p78wg wrote

The best way to learn anything (also deep learning), especially for beginners, tends to be IMO to follow some structured approach and stick to it. So pick a good book or course and try to finish it (or the fundamental parts). It may take a bit longer to see progress than randomly following youtobe tutorials or notebooks, but builds a solid base that makes learning in the mid/long term more efficient.

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tartenpi0n t1_j5qvv9e wrote

I personally started DeepLearning with this free course : Intro to DeepLearning with Pytorch and I really recommend it. It's long but you don't have to finish it entirely to understand key principles. This course does not learn how to deal with segmentation tasks, but one you've understand key principles of DeepLearning, you will understand any blogpost on segmentation.

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FastestLearner t1_j5ogton wrote

It actually depends on what you want to achieve. For example, if you want to do research in DL, the best way is not to start with DL at all and instead do some fundamental math courses like LinAlg, Prob/Stats, Intermediate and Advanced Calc, etc., then turn to traditional ML, and only after that you do DL. This is the bottom-up approach and it is a long journey that takes years. But from your post, it seems that you are looking for a quick top-down approach. For that, I would suggest you simply look into some medium.com articles, youtube videos, udemy courses and most importantly the dive head first into coding (try running as many examples from github as you can). Try reproducing some basic results, like getting >90% accuracy on CIFAR-10 classification with a ResNet model. You could also try getting into a bootcamp if there's one going on nearby.

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Final-Rush759 t1_j5rkm71 wrote

The best way to learn is to go through tutorials from various source just to get a feel of what's like to do ML and DL. Then go through the theory including data pipeline, target, models, loss function, gradient, optimizer etc.

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EnlightenMePlss t1_j5tzjo3 wrote

Check out the relevant kaggle competitions and study the most popular notebooks for it:

https://www.kaggle.com/c/tumor-diagnosis
https://www.kaggle.com/c/rsna-miccai-brain-tumor-radiogenomic-classification

Also checkout the other RSNA competitions:

https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection
https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge
https://www.kaggle.com/competitions/rsna-str-pulmonary-embolism-detection
https://www.kaggle.com/competitions/rsna-intracranial-hemorrhage-detection
https://www.kaggle.com/competitions/rsna-miccai-brain-tumor-radiogenomic-classification
https://www.kaggle.com/competitions/rsna-breast-cancer-detection

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SevereSupermarket244 t1_j5w9w7r wrote

How can I see the code? Of the first link for example?

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EnlightenMePlss t1_j5y57ce wrote

The first link seems to have no code. But for the others just click on "code". Then you can sort the public notebooks by "most votes", "best score", etc. and have a look at them.

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SevereSupermarket244 t1_j5w9k7u wrote

For introduction watch Andrew Nga course about Deep Learning on YT and then do what @EnlightenMePIss suggests

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JJJJJJtti t1_j5oe17b wrote

There's this thing called google where you can insert text, type 'deep learning' and, after that, press the search button. You'll be amazed by how many results you'll get in a fraction of a second. Then you click on, say, a blog post, you start reading it. The first technical word that you see and don't know what it means you select it, right click it and press 'Search 'word' with google' and open whatever file that seems plausible. Do this for all unknown words on all posts, articles, papers, videos until your recursion ends. Also, don't forget to get your hands dirty!

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cyranix t1_j5s8lbz wrote

While this comment is getting a handful of downvotes (probably for its sarcastic tone), I do want to add something here: Personally, I think the best way to learn is by doing, and there are a lot of really great tutorials on things you can do with deep learning (yes, you can find them by doing a google search), however I found that I was really taxing my laptop trying to do some of the tutorials for instance from sentdex... BUT it turns out that Google has a research platform you can use for FREE that gives you access to GPUs and TPUs specifically for the purposes of doing ML tasks... So check out that channel, and then check out https://colab.research.google.com/ for a great platform to start putting your code together!

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