Recent comments in /f/deeplearning

agentfuzzy999 t1_j5qy82t wrote

Reply to Best cloud to train models with 100-200 GB of data? by Zealousideal-Copy463

“Should I just buy a 4090”

Ok Jeff Bezos

4090 clock speed is going to be faster than similar instances that use T4s, plus wayyyyyyy more CUDA cores. Training will be significantly faster, if you can fit the model on the 4090. If you can “business expense” a 4090 for your own machine, good lord do that.

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tartenpi0n t1_j5qvv9e wrote

Reply to What are the best ways to learn about deep learning? by Tureep

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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suflaj t1_j5qb32y wrote

Reply to Efficient way to tune a network by changing hyperparameters? by NinjaUnlikely6343

There is this: https://www.microsoft.com/en-us/research/blog/%C2%B5transfer-a-technique-for-hyperparameter-tuning-of-enormous-neural-networks/

However, it's unlikely to help in your case. The best thing you can do is grid search if you know something about the problem, or just random search. I prefer random search even if I'm am expert for the problem, ESPECIALLY with ML models.

But I'm curious how it takes a long time. You don't have to train the whole dataset. Take 10% for training and 10% for validation, or less if that dataset is huge. You just need enough data to learn something. Then your optimal hyperparameters are a good enough approximation.

Also, it might help to just not tune redundant hyperparameters. Layer sizes are usually such, as is almost any hyperparameter in the Adam family of optimizers besides learning rate and to a lesser extent first momentum. Which ones are you optimizing?

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SimulatedAnnealing t1_j5p78wg wrote

Reply to What are the best ways to learn about deep learning? by Tureep

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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FastestLearner t1_j5ogton wrote

Reply to What are the best ways to learn about deep learning? by Tureep

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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JJJJJJtti t1_j5oe17b wrote

Reply to What are the best ways to learn about deep learning? by Tureep

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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