gs-quant VS notebooks

Compare gs-quant vs notebooks and see what are their differences.

notebooks

Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers. (by differential-machine-learning)
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gs-quant notebooks
96 1
2,420 132
6.0% -
7.9 10.0
11 days ago over 1 year ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

gs-quant

Posts with mentions or reviews of gs-quant. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning gs-quant yet.
Tracking mentions began in Dec 2020.

notebooks

Posts with mentions or reviews of notebooks. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning notebooks yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing gs-quant and notebooks you can also consider the following projects:

fastquant - fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!

FinancePy - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.

resistance - Pre-crisis Risk Management for Personal Finance

hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:

MEDIUM_NoteBook - Repository containing notebooks of my posts on Medium

Mad-Money-Backtesting - Backtesting recommendations from Mad Money and "The Cramer Effect/Bounce"

fastbook - The fastai book, published as Jupyter Notebooks

fastai - The fastai deep learning library