sysgeass's Stars
benfulcher/hctsa
Highly comparative time-series analysis
robertmartin8/MachineLearningStocks
Using python and scikit-learn to make stock predictions
mfrdixon/Deep_Fundamental_Factors
Source code for Deep Fundamental Factor Models, https://arxiv.org/abs/1903.07677
skolouri/swgmm
Sliced Wasserstein Distance for Learning Gaussian Mixture Models
Yubo02/Wasserstein-K-means-for-clustering-probability-distributions
There are the codes needed for the paper: Wasserstein K-means for clustering probability distributions
bukosabino/ta
Technical Analysis Library using Pandas and Numpy
jakobrunge/tigramite
Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at
microsoft/qlib
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
xinychen/transdim
Machine learning for transportation data imputation and prediction.
juliansester/Robust-Portfolio-Optimization
Markov decision processes under model uncertainty
stefan-jansen/machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
nathanrooy/differential-evolution-optimization
A simple, bare bones, implementation of differential evolution optimization.
milsto/differential-evolution
Single header c++ implementation of Differential Evolution algorithm for general purpose optimization.
kamperh/bayes_gmm
Bayesian Gaussian mixture models in Python.
hugo2046/QuantsPlaybook
量化研究-券商金工研报复现
open-mmlab/mmselfsup
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
Gogh-Co/Gogh
Gogh is a collection of color schemes for various terminal emulators, including Gnome Terminal, Pantheon Terminal, Tilix, and XFCE4 Terminal also compatible with iTerm on macOS.
rakr/vim-one
Adaptation of one-light and one-dark colorschemes for Vim
kirit93/GRU
A C++ implementation of a 3 layer Gated Recurrent Unit (GRU) using no libraries other than Eigen for Matrices.
deepakrana47/GRU_implementation
Gated Recurrent Unit implementation from scratch
robertmartin8/PyPortfolioOpt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
nicodjimenez/lstm
Minimal, clean example of lstm neural network training in python, for learning purposes.
nanguoshun/HMM
A C++ implementation of Hidden Markov Model
lmedeiro/fe_and_pm_for_financial_time_series
Feature Engineering and Predictive Modeling for Financial Time Series Data
koba-jon/svm_cpp
Support Vector Machines Implementation from scratch in C++
codestorm04/Arma_ML
high performance statistic machine learning libraries in C++ [based on Armadillo-9.300]
outlace/OpenTDA
Open source Python library for topological data analysis (TDA)
RedditSota/state-of-the-art-result-for-machine-learning-problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
afatcoder/LeetcodeTop
汇总各大互联网公司容易考察的高频leetcode题🔥
liguigui/CyC2018-CS-Notes