https://www.trymito.io/
Or maybe
(Paraphrasing https://en.wikipedia.org/wiki/Jamie_Zawinski#Zawinski's_Law and https://en.wikipedia.org/wiki/Greenspun%27s_tenth_rule if you didn't recognize them at once. 😊)
Though curious thing about this tool is that it generates Python code that performs transformations you specify in the spreadsheet. Advantages are obvious. Would be super cool if it could synchronize the other way round, but it can't unfortunately.
#datascience #jupyter #python
Every Data Analysis platform attempts to expand until it includes a Spreadsheet. Those platforms which cannot so expand are replaced by ones which can.
Or maybe
Any sufficiently complicated Data Analysis platform contains an ad hoc, informally-specified, bug-ridden, slow implementation of half of Excel.
(Paraphrasing https://en.wikipedia.org/wiki/Jamie_Zawinski#Zawinski's_Law and https://en.wikipedia.org/wiki/Greenspun%27s_tenth_rule if you didn't recognize them at once. 😊)
Though curious thing about this tool is that it generates Python code that performs transformations you specify in the spreadsheet. Advantages are obvious. Would be super cool if it could synchronize the other way round, but it can't unfortunately.
#datascience #jupyter #python
www.trymito.io
Best Python Spreadsheet Automation & Code Generation | Mito
Mito is the fastest way to do Python data science. Edit your data in a spreadsheet, and generate Python code automatically.
https://dp.quantecon.org/
A #free #book on "Dynamic Programming" authored by Thomas J. Sargent (who got a Nobel Prise in macroeconomics) and John Stachurski.
It's a strange kind of "Dynamic Programming", the topics include:
— Fixed points and order
— Markov models
— Optimal stopping
— Markov decision processes
— State dependent discounting
— Nonlinear valuation
— Abstract dynamic programming
Examples are in #Julia and #Python
A #free #book on "Dynamic Programming" authored by Thomas J. Sargent (who got a Nobel Prise in macroeconomics) and John Stachurski.
It's a strange kind of "Dynamic Programming", the topics include:
— Fixed points and order
— Markov models
— Optimal stopping
— Markov decision processes
— State dependent discounting
— Nonlinear valuation
— Abstract dynamic programming
Examples are in #Julia and #Python
❤5
https://www.stochasticlifestyle.com/chatgpt-performs-better-on-julia-than-python-and-r-for-large-language-model-llm-code-generation-why/
Evidently ChatGPT 3.5 "understands" #Julia significantly better than other languages including Python and JavaScript, not even mentioning Go, C and C++: https://arxiv.org/abs/2308.04477
Chris Rackauckas gives some points as to why it's not that surprising from the perspective of teaching novices. And also speculates that large volume of so-so tutorials and examples for very popular languages might hurt LLMs' learning.
He also advertises his
Evidently ChatGPT 3.5 "understands" #Julia significantly better than other languages including Python and JavaScript, not even mentioning Go, C and C++: https://arxiv.org/abs/2308.04477
Chris Rackauckas gives some points as to why it's not that surprising from the perspective of teaching novices. And also speculates that large volume of so-so tutorials and examples for very popular languages might hurt LLMs' learning.
He also advertises his
diffeqpy library connecting optimized solvers implemented in Julia (including code generation for GPUs) to #Python #machinelearning libraries, and points to some curious papers with impressive benchmarks. 😊Stochastic Lifestyle
ChatGPT performs better on Julia than Python (and R) for Large Language Model (LLM) Code Generation. Why? - Stochastic Lifestyle
Machine learning is all about examples. The more data you have, the better it should perform, right? With the rise of ChatGPT and Large Language Models (LLMs) as a code helping tool, it was thus just an assumption that the most popular languages like Python…
👏2🤔1