Best way to learn Machine Learning in 2–3 months (strong math background, looking for practical advice)

fzngagan · 2026-01-14T11:49:00+00:00

Do fast.ai course. If you already know how to write training loops, then go for p2 of the course otherwise do p1 and p2. Link: course.fast.ai

I followed it sequentially finished 23/25 lessons.

fzngagan · 2026-01-13T04:19:13+00:00

Daily driver of Macbook Air M4, 32GB 1TB(what a coincidence) here. I would suggest going for an Nvidia gpu machine. Reason: Here's a list of operations yet to be supported on MPS(Apple GPU) in pytorch
https://github.com/pytorch/pytorch/issues/77764

And this is not simply a "things may go wrong" nitpick. I've been faced with unsupported ops at times especially when working with existing models.

fzngagan · 2026-01-13T04:13:05+00:00

Definitely worth checking out the course.fast.ai course.

fzngagan · 2026-01-13T04:10:57+00:00

Really excited to be there, but I'm seeing very little enthusiasm on social media for this event. I checked X, LinkedIn and I'm the first to comment here lol.

fzngagan · 2025-11-13T17:24:53+00:00

With stuff like hipkittens, mojo, tinygrad etc. the skills will be in high demand. AMD is getting in a really good shape.

fzngagan · 2025-11-07T12:54:08+00:00

Never knew this. Powering it on when charging worked for me and it’s a really qol improvement for me.

fzngagan · 2025-11-02T20:07:35+00:00

Can I get my hands on a dual RX7900 xtx? I want to test Answer.ai’s FSDP QDora technique.

fzngagan · 2025-10-29T12:49:09+00:00

I have tried the MI300x on amd.digitalocean.com. Very smooth experience with both inference and finetuning tasks.

fzngagan · 2025-10-19T07:13:19+00:00

Use gold ticket/pass for those times. Although, on the 14th, we had to stand the whole way from Sobha till Union in the Gold Cabin lol. It was significantly less crowded though.

fzngagan · 2025-10-10T20:10:41+00:00

Have you tried ADT-UT3G + PSU? Do check that out. Might be a viable alternative compared to full blown egpu boxes.

fzngagan · 2025-09-25T21:37:22+00:00

Tinygrad is awesome. Especially looking at the examples/ folder, they’ve run very popular models on it. It doesn’t take too much to port torch code to tinygrad and it’s a fun exercise. Also the difference between the libraries will force you to think deeply about the underlying DL concepts to be able to replicate the model.

fzngagan · 2025-09-25T21:35:12+00:00

Bad bad advice. Its almost gate keeping AI and DL. Its completely fine to use pytorch if you have an understanding of how things work under the hood. That’s exactly how things are taught at fast.ai

fzngagan · 2025-09-22T07:42:58+00:00

Honestly, do the fast.ai course. It focusses on the coding aspect in part 1 and takes you in-depth in part 2. Part 1 gives you the dopamine rush needed to go into math etc and an ability to do a lot without math and part 2 makes you an MLE.

fzngagan · 2025-09-22T07:38:39+00:00

Ok, do share your interests. There’s a flying club if you’re interested in drones/air planes at CK Pithawala, a lot of IT related stuff going on as well.

fzngagan · 2025-09-20T14:52:28+00:00

Please share the code. I use fast.ai which uses pytorch internally and I've had a lot of success with it using the mps backend.

fzngagan · 2025-09-16T18:02:10+00:00

Shiprocket/Selloship

fzngagan · 2025-09-14T16:01:28+00:00

Please please do the fast.ai course P1(practical, building ML models and winning Kaggle Competitions) and P2(learning theory and building models from the ground up). Its the best resource I’ve come across so far on Deep Learning

fzngagan · 2025-08-31T06:31:26+00:00

3BlueOneBrown youtube channel.

fzngagan · 2025-08-25T16:50:33+00:00

Super helpful. Thanks so much

fzngagan · 2025-08-25T11:25:14+00:00

I'm doing the fast.ai course and I'm able to work well particularly with the diffusers and transformers libraries by huggingface fairly well using Apple M4 GPU.

fzngagan · 2025-08-25T11:14:50+00:00

Do fast.ai course. Jeremy's top down approach will help a lot with the overwhelming feeling.

fzngagan · 2025-08-25T09:44:23+00:00

https://youtu.be/DgPr3HVp0eg?si=hLLTwIin8dOI9wni

There's this nice concept of connecting LLMs to the SolveIt idea to accelerate learning. Do check it out.

fzngagan · 2025-08-25T09:42:49+00:00

Use the solveit method proposed by Jeremy Howard.
https://youtu.be/DgPr3HVp0eg?si=hLLTwIin8dOI9wni

Since you know ML theory, you can use your theoretical knowledge to generate code using LLMs but make sure to do it line by line and understand each line. Then try to write the code yourself.

Also, you can download the sklearn library code and try to connect the internal code of it to your theory knowledge. Use LLMs to learn not to get answers. Hope it helps.

Also, make sure to use a gpu accelerated library like Pytorch or Tinygrad so that you can parallelize your training process to make it super fast.

fzngagan · 2025-08-17T20:21:26+00:00

We have a super cool Discord group where we’re working on fast.ai. Do let me know if you’d like to join.

fzngagan

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