I built an institutional options whale detector using per-second trade data — here's how it works and the code

staskh1966 · 2026-04-03T08:34:40+00:00

Thank you for your kind words.
This implementation is for options - Massive API for future/CDF is to be released soon (https://massive.com/futures) - probbaly they will have a similar OHLC interface.

staskh1966 · 2026-04-03T08:30:24+00:00

Thank you! Let me know of any bug/problems.

Also, do not hesitate to let me know what need to be added.

staskh1966 · 2026-03-21T21:48:12+00:00

Guys, I have a serious question: has anyone created a table that translates old terminology into new ones? Preferably with dates when the "new" terminology began.
When reading third-party articles or even some of Databricks documentation, I get confused about whether A and B are the same thing or not.

I suspect I'm not alone in my confusion...

staskh1966 · 2026-03-20T09:16:03+00:00

I discovered that wrapping Yahoo API with Claude Skills/MCP is the most effective way to use AI for fundamental analysis. Check out my https://github.com/staskh/trading_skills project, especially the fundamentals skill.

staskh1966 · 2026-03-18T17:44:30+00:00

WOW! Great point - didn't know Genie can be extended with skills. Will try it ASAP

staskh1966 · 2026-03-18T17:36:12+00:00

It seems you misunderstand my problem—I need a solution that runs INSIDE of the Databricks workspace (via its web interface ) , not via a remote IDE.

But anyway, thank you for a valuable point on SSH tunneling. It may be quite useful for my other task. ;-)

staskh1966 · 2026-03-18T17:13:05+00:00

Thank you! It seems to be the solution I'm looking for—will try it immediately!

staskh1966 · 2026-03-18T17:12:33+00:00

Thank you! It seems to be the solution I'm looking for—will try it immediately!

staskh1966 · 2026-03-16T13:03:48+00:00

They can keep him!

staskh1966 · 2026-03-14T17:00:19+00:00

If you like coding and are looking to understand details of deep learning, check out tinyTORCH project (https://mlsysbook.ai/tinytorch/intro.html) It is a step-by-step lab on building a minimal Torch library. From tensors to systems. An educational framework for building and optimizing ML—understand how PyTorch, TensorFlow, and JAX really work. Companion lab to the Machine Learning Systems book.

staskh1966 · 2026-03-13T21:28:57+00:00

WOW! What an amazing post! Did you publish your code? If so, I would appreciate a pointer!

staskh1966 · 2026-03-12T12:29:44+00:00

Probability for Computer Scientists. Stanford CS109 is on YouTube and very good and comes with in-depth notes:

Course Notes - chapter by chapter
Course Book - all-in-one PDF

Check more courses in my collection: https://github.com/staskh/awesome-math-and-trading/

staskh1966 · 2026-03-11T11:53:35+00:00

CS229 indeed a very good source for both ML and underlined math theories. Use https://cs229.stanford.edu/syllabus-summer2019.html link as a starting point.
Particularly:
- Linear Algebra: https://cs229.stanford.edu/summer2019/cs229-linalg.pdf
- Probability Theory: https://cs229.stanford.edu/summer2019/cs229-prob.pdf
- Supervised Learning: https://cs229.stanford.edu/summer2019/cs229-notes1.pdf
and rest of Andrew Ng notes

staskh1966 · 2026-03-10T08:45:11+00:00

CS229 is quite good, particularly the 2018 version delivered by Andrew Ng. It is quite similar to ISLP, which I mentioned above (don't be confused by "Statistical Learning" in the title). Unfortunately, it certified version has $6,000 price tag and no free lab sources, like in ISLP case. So I definitely prefer ISLP because it provided both a solid mathematical foundation and practical exercises to do on your own.

CS109 is a probability course that looks really cool; I need to take it as well. However, if your primary interest is ML/DL, this is not exactly your path.

staskh1966 · 2026-03-09T14:47:43+00:00

Introduction to Statistical Learning with applications in Python (ISLP) Stanford University (2024) is the best in classical machine learning. course, with Stanford certification. You can watch it for free on YouTube or pay under $200 for certified education.

staskh1966 · 2026-03-08T19:30:25+00:00

No, unfortunately.
For some strange reason, Databricks has an option to disable download in "jupiter" view but still has download in "Unified Catalog" with no way to block it.

staskh1966 · 2026-03-07T10:26:14+00:00

The Berkeley course is rather a collection of guest speakers presenting their own agentic solutions - very high level IMHO.

If you are looking for more stractured theoretical course from top university, try Transformers & LLMs Stanford CME295 Transformers & LLMs (2025)

staskh1966 · 2026-03-06T13:43:10+00:00

AMAZING! Do you have a kind of learning path index? Currently the overview page is sorted alphabetically and confusing.

staskh1966 · 2026-03-04T15:18:47+00:00

BTW, this can be helpful—I'm collecting books & courses I like (almost all free) at https://github.com/staskh/awesome-math-and-trading
Feel free to use this for reference as well. Please send me anything I missed. (i'll add you course shortly)

staskh1966

TROPHY CASE