jjbrophy47

jjbrophy47's Stars

• EthicalML/awesome-production-machine-learning

  A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

  17.8k408782.3k

• visenger/awesome-mlops

  A curated list of references for MLOps

  12.7k395161.9k

• ydataai/ydata-profiling

  1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

  Language:Python12.6k1528151.7k

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Language:C++6.3k146453737

• awslabs/gluonts

  Probabilistic time series modeling in Python

  Language:Python4.7k77962763

• kelvins/awesome-mlops

  :sunglasses: A curated list of awesome MLOps tools

  Language:Python4.2k897580

• jphall663/awesome-machine-learning-interpretability

  A curated list of awesome responsible machine learning resources.

  3.7k13569591

• paperswithcode/releasing-research-code

  Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

  2.6k566717

• instill-ai/instill-core

  🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications

  Language:Makefile2.2k30519109

• feature-engine/feature_engine

  Feature engineering package with sklearn like functionality

  Language:Python2k33328316

• stanfordmlgroup/ngboost

  Natural Gradient Boosting for Probabilistic Prediction

  Language:Python1.7k45210222

• thunlp/TAADpapers

  Must-read Papers on Textual Adversarial Attack and Defense

  Language:Python1.5k5413194

• wangyongjie-ntu/Awesome-explainable-AI

  A collection of research materials on explainable AI/ML

  Language:Markdown1.4k428199

• skrub-data/skrub

  Prepping tables for machine learning

  Language:Python1.3k22368107

• skforecast/skforecast

  Time series forecasting with machine learning models

  Language:Python1.2k9186143

• Nixtla/mlforecast

  Scalable machine 🤖 learning for time series forecasting.

  Language:Python9301315891

• jjbrophy47/machine_unlearning

  Existing Literature about Machine Unlearning

  81125799

• StatMixedML/XGBoostLSS

  An extension of XGBoost to probabilistic modelling

  Language:Python572274360

• polyaxon/traceml

  Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

  Language:Python510141443

• StatMixedML/LightGBMLSS

  An extension of LightGBM to probabilistic modelling

  Language:Python285112628

• elephaint/pgbm

  Probabilistic Gradient Boosting Machines

  Language:Python14482320

• StatMixedML/CatBoostLSS

  An extension of CatBoost to probabilistic modelling

  14214913

• Mcompetitions/M6-methods

  Data, Benchmarks, and methods submitted to the M6 forecasting competition

  Language:Jupyter Notebook10419134

• jjbrophy47/tree_influence

  Influence Estimation for Gradient-Boosted Decision Trees

  Language:Python264410

• StatMixedML/DGBM

  Distributional Gradient Boosting Machines

  26721

• jjbrophy47/dare_rf

  Machine Unlearning for Random Forests

  Language:Python17213

• jjbrophy47/instance_based_interpretability

  Existing literature about training-data analysis.

  17201

• REACT-NLP/tcab_generation

  Code to generate and extend the TCAB dataset.

  Language:Python3110

• REACT-NLP/tcab_benchmark

  Code to train baseline models for the TCAB benchmark.

  Language:Python2100