richardskim111

richardskim111's Stars

• ranaroussi/quantstats

  Portfolio analytics for quants, written in Python

  Language:Python5.1k116264873

• polakowo/vectorbt

  Find your trading edge, using the fastest engine for backtesting, algorithmic trading, and research.

  Language:Python4.5k126454626

• matplotlib/mplfinance

  Financial Markets Data Visualization using Matplotlib

  Language:Python3.7k94531638

• quantopian/research_public

  Quantitative research and educational materials

  Language:Jupyter Notebook2.5k206191.6k

• PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition

  Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

  Language:Jupyter Notebook2k11001k

• ranahanocka/MeshCNN

  Convolutional Neural Network for 3D meshes in PyTorch

  Language:Python1.6k47157321

• PythonCharmers/QuantFinance

  Top training materials in quantitative finance

  Language:Jupyter Notebook397268138

• ProteoWizard/pwiz

  The ProteoWizard Library is a set of software libraries and tools for rapid development of mass spectrometry and proteomic data analysis software.

  Language:C#23916289100

• jamesrobertlloyd/gpss-research

  Kernel structure discovery research code - likely to be unstable

  Language:TeX190196073

• uuazed/numerapi

  Python API and command line interface for the numer.ai machine learning competition

  Language:Python177164472

• dysonance/Strategems.jl

  Quantitative systematic trading strategy development and backtesting in Julia

  Language:Julia162252138

• pckroon/pysmiles

  A lightweight python-only library for reading and writing SMILES strings

  Language:Python15042321

• crowdcent/numerblox

  Solid Numerai pipelines

  Language:Python11361710

• IQVIA-ML/LightGBM.jl

  Julia FFI interface to Microsoft's LightGBM package

  Language:Julia9355610

• PacktPublishing/Algorithmic-Short-Selling-with-Python

  Algorithmic Short Selling with Python, Published by Packt

  Language:Jupyter Notebook8911062

• lucas-campagna/mt5linux

  MetaTrader5 for linux users

  Language:Python8582047

• JuliaQuant/TradingLogic.jl

  Backtesting and trading with Julia reactive programming.

  Language:Julia63171422

• iomega/spec2vec

  Word2Vec based similarity measure of mass spectrometry data.

  Language:Python6275416

• matchms/ms2deepscore

  Deep learning similarity measure for comparing MS/MS spectra with respect to their chemical similarity

  Language:Jupyter Notebook57411525

• degerhan/dsignals

  Utilities and information for the signals.numer.ai tournament

  Language:Python243111

• s-broda/ComputationalFinance

  Code for the MSc Finance course "Computational Finance" at U Amsterdam

  Language:Jupyter Notebook243031

• OpenXAIProject/Relational-Automatic-Statistician

  Expainable Baysian Models for Smooth Time Series Datasets (modified)

  Language:MATLAB21205

• phnmnl/container-pwiz

  The ProteoWizard Library and Tools are a set of modular and extensible open-source, cross-platform tools and software libraries that facilitate proteomics data analysis, developed by the Proteowizard Team at http://proteowizard.sourceforge.net/. This repository contains the Docker image to convert from many vendor raw data formats to mzML via Linux WINE.

  Language:HTML212208

• biosustain/pyOpenMS_UmetaFlow

  Untargeted metabolomics workflow for data processing and analysis written in Jupyter notebooks (Python)

  Language:Jupyter Notebook18657

• antonvsdata/notame

  An R package for non-targeted LC-MS metabolomics

  Language:R16392

• lobingera/Rsvg.jl

  adaptation of the rsvg lib

  Language:Julia1521913

• ProteoWizard/container

  Options for running ProteoWizard applications via containers (e.g. Docker)

  Language:Dockerfile98148

• anne-susann/CoCultureSmPp

  Analysis of the MS1 and MS2 data of Co-Culture experiment with S. marinoi and P. parvum

  Language:R21

• anne-susann/MAW

  Metabolome Annotation Workflow

  Language:Jupyter Notebook1

• RetuWonData/notame_examples

  A set of short instructional scripts to bring out the best from notame

  Language:R1