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A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
A guidance language for controlling large language models.
Collection of notebooks about quantitative finance, with interactive python code.
A scikit-learn compatible neural network library that wraps PyTorch
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
Technical Analysis Library using Pandas and Numpy
Performance analysis of predictive (alpha) stock factors
TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's …
A Haskell kernel for the Jupyter project.
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
Financial data reader
Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SP…
Coursera Machine Learning - Python code
A python library for time-series smoothing and outlier detection in a vectorized way.
All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
Mostly experiments based on "Advances in financial machine learning" book
A clean book theme for scientific explanations and documentation with Sphinx
Python library for identifying the peaks and valleys of a time series.
Library for fitting the LPPLS model to data.
This Jupyter Notebook will help you downloading Coursera videos, subtitles and quizzes (but not answering the quiz). It will automatically download and convert vtt subtitle files into srt. All reso…
Samples code demonstrating how to use IbPy to extract information from Interactive Brokers API
Scanner that finds patterns in stocks/options/futures and discerns future risk/reward. Ie, money ball engine.
Limit Orderbook Replay/Analysis Library
import ReST (*.rst) includes into monolytic file, to be able to dispay it on Github and PyPi
ByteSumoLtd / pyESN
Forked from cknd/pyESNEcho State Networks in Python, with Activations on the Hyper-Sphere, for DEAP based AutoML
Neural Network, Linear & Logistic Reression, Random Forests and more implementations. Examples and explanations.