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A regression solver for linear and quantile regression models and lasso based penalizations'
:atom: The hackable text editor
A curated list of awesome Machine Learning frameworks, libraries and software.
Barra CNE6 因子构建
A risk evaluation program that follows BARRA's CNE6 and USE4 risk model to predict the risk and distribution of factors in a portfolio. Created by Rosemary He Sept. 2019, under Zhiqiang Zhang.
以wind为数据源的基金单期brinson业绩归因
Resources for using NLP on central bank communications
In this repository, I will apply NLP techniques to central banks speeches.
A Python-embedded modeling language for convex optimization problems.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Principal Component Analysis (PCA) for Missing and/or Noisy Data
Variance-based Feature Importance in Neural Networks
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Hidden Markov Models in Python, with scikit-learn like API
LightGBM, XGboost, Random Forest, Stacking, Feature Selection (PCA, correlation, feature importance)
Data imputations library to preprocess datasets with missing data
TeX templates for academic journal, presentation, problem set, and cheat sheet
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
A new code framework that uses pytorch to implement meta-learning, and takes Meta-Weight-Net as an example.
A final project to research the European Central bank's green economy supports by using NLP
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.
A modification in the traditional random forest feature selection method which uses less memory usually for instances where dataset is not loadable in the memory.
Code for "Is There a Replication Crisis in Finance" by Jensen, Kelly and Pedersen (2022)
Quantitative research and educational materials
The practitioner's forecasting library
Sequence learning toolkit for Python
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.