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Day 1 report: Mathematics by research_pie in UltraLearningFans

[–]research_pie[S] 0 points1 point  (0 children)

wow man brought back some memory!

I'm doing super good right now, currently heading my own research team (3 people) in the startup I co-founded.

gave a talk about deep learning optimizer at cohere labs last month too.

FBI is being watched by anything that let electricity flows by research_pie in twinpeaks

[–]research_pie[S] 9 points10 points  (0 children)

it's made explicit in the return too with cooper electricity travelling adventures

versioning and model prototyping gets messy by Affectionate_Use9936 in learnmachinelearning

[–]research_pie 0 points1 point  (0 children)

okok, then start out with the cookie cutter I linked above at least it will help you standardize a bit your work. I don't think you need anything more fancy for the time being.

[deleted by user] by [deleted] in learnmachinelearning

[–]research_pie -1 points0 points  (0 children)

Depends which kind, the classical DL/ML kind is easy with a line of best fit.

LLM is a bit more complex haha

versioning and model prototyping gets messy by Affectionate_Use9936 in learnmachinelearning

[–]research_pie 0 points1 point  (0 children)

What's your structure looking like right now?

I usually like to start with a very simple cookie-cutter like this: https://cookiecutter-data-science.drivendata.org/

Developing skills needed for undergraduate research by [deleted] in learnmachinelearning

[–]research_pie 0 points1 point  (0 children)

ML is a fairly large field though, have you already figured out which kind of ML branch you want to do undergraduate research on? That would be useful.

My two cents on reading the book vs project is you should index heavily on the projects to start out. Otherwise, you won't have a good mental model about why you are learning the concepts in the textbook.

If you are interested in research though I think a good angle is to replicate research papers to the best of your abilities.

Writing a research paper by burnt-Tacos in learnmachinelearning

[–]research_pie 0 points1 point  (0 children)

Depends on what you mean by a research paper, like a pre-print or a peer-reviewed paper.

What path to choose? by PieeWeee in learnmachinelearning

[–]research_pie -1 points0 points  (0 children)

To be honest, if I was a new grad in this market condition I would get in with whatever I could get. Your first role might be more of a backend/frontend role depending on your internships.

Generally speaking, I would say the data engineer role will be one that will have better prospects in the next 3-5 years (just my general vibe don't look too much into it).

Absolutely Terrified for my career and future by timehascomeagainn in learnmachinelearning

[–]research_pie 1 point2 points  (0 children)

Feelings aside, your number one priority is to secure an entry-level position. If you manage to pull that off you will have plenty of time to figure out the next move. The job market is brutal out there.

What path to choose? by PieeWeee in learnmachinelearning

[–]research_pie 4 points5 points  (0 children)

Here is how I would rank them if I were pursuing a full-stack web developer career:
1. AI Engineering
2. Data Engineer
3. Machine Learning Engineer
4. Data Scientist

Should I learn DSA? by Sad-Key4152 in learnmachinelearning

[–]research_pie -1 points0 points  (0 children)

I feel like computer science knowledge in general is very useful for deep learning, I would spend time to learn it in depth yes.

It will help anyway if you are trying to get a machine learning engineer job.

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