Joearrowsmith

Joearrowsmith's Stars

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  27.6k291432.3k

• eugeneyan/applied-ml

  📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

  27.4k949243.7k

• d2l-ai/d2l-en

  Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

  Language:Python24.3k4192964.4k

• mlflow/mlflow

  Open source platform for the machine learning lifecycle

  Language:Python19.1k3054k4.3k

• 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.

  Language:Python15.8k3019192.7k

• google-deepmind/deepmind-research

  This repository contains implementations and illustrative code to accompany DeepMind publications

  Language:Jupyter Notebook13.4k3253262.6k

• facebookresearch/hydra

  Hydra is a framework for elegantly configuring complex applications

  Language:Python8.9k1301.4k644

• MIC-DKFZ/nnUNet

  Language:Python6.1k762.1k1.8k

• vwxyzjn/cleanrl

  High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

  Language:Python6k38186674

• chrisconlan/algorithmic-trading-with-python

  Source code for Algorithmic Trading with Python (2020) by Chris Conlan

  Language:Python2.8k10110508

• rentruewang/koila

  Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.

  Language:Python1.8k122863

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

  Machine Learning for Algorithmic Trading, Second Edition - published by Packt

  Language:Jupyter Notebook1.3k7016495

• dwcoder/QuantitativePrimer

  An Interview Primer for Quantitative Finance

  Language:TeX1.2k396165

• tensorflow/decision-forests

  A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

  Language:Python66624165112

• google-research/sam

  Language:Python57191872

• google/yggdrasil-decision-forests

  A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

  Language:C++5081510654

• zslucky/algorithmic_trading_book

  2 books and related source codes for algorithmic trading.

  Language:Python434110190

• Lux-AI-Challenge/Lux-Design-S2

  Repository for the Lux AI Challenge, season 2 (NeurIPS 23). Hosted on @kaggle

  Language:Jupyter Notebook40717121144

• PythonCharmers/QuantFinance

  Top training materials in quantitative finance

  Language:Jupyter Notebook398268138

• iosband/ts_tutorial

  Language:Jupyter Notebook3539592

• uchidalab/time_series_augmentation

  An example of time series augmentation methods with Keras

  Language:Jupyter Notebook3398569

• loeweX/Greedy_InfoMax

  Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations

  Language:Python285161436

• loeweX/Forward-Forward

  Reimplementation of Geoffrey Hinton's Forward-Forward Algorithm

  Language:Python1354629

• AlxndrMlk/causality

  Notes, exercises and other materials related to causal inference, causal discovery and causal ML.

  Language:Jupyter Notebook1317031

• sustainable-processes/ORDerly

  Chemical reaction data & benchmarks. Extraction and cleaning of data from Open Reaction Database (ORD)

  Language:Python725708

• jambo6/generalised-signature-method

  Code for: "A Generalised Signature Method for Time Series"

  Language:Python593310

• mozilla/snakepit

  Machine learning job scheduler

  Language:JavaScript511316516

• loeweX/ComplexAutoEncoder

  Code for the paper: Complex-Valued Autoencoders for Object Discovery

  Language:Python47208

• ayulockin/DataAugmentationTF

  Implementation of modern data augmentation techniques in TensorFlow 2.x to be used in your training pipeline.

  Language:Jupyter Notebook352012

• jjccero/DvD_TD3

  The implementation of DvD-TD3.

  Language:Python4100