QuasiAlon

Explained by example: whenever I learn something new, say, a new machine learning model and its implementation in Python, I create or update a Jupyter Notebook, write my notes as text, add the relevant snippets and run them on locally stored dummy data. This proved useful for me with Python.

I need an effective system for other things, like SQL, or generally anything I learn or need to keep track of for future reference. I tried google docs, sheets, even slides, txt files (with my always open sublime text), etc. etc. I find my stuff is scattered all over the place and isn't very productive or efficient.

Any insights?

Hi, An opportunity presented itself to do some consulting work for a startup in NYC (working remotely). I'm a data scientist with a few years experience. Always worked full time as a salary man, so don't know how I should price my time, what factors to consider and how to settle on an hourly rate.

(side note: I tried looking for going rates of US data scientists on freelancing websites like upwork, but the hourly rates are all over the place, from $20 to $200).

Appreciate your insights!