nbrosse's Stars
whylabs/whylogs
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
Mishima-syk/py4chemoinformatics
Python for chemoinformatics
dmlc/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
awslabs/dgl-lifesci
Python package for graph neural networks in chemistry and biology
sokrypton/ColabFold
Making Protein folding accessible to all!
CalculatedContent/WeightWatcher
The WeightWatcher tool for predicting the accuracy of Deep Neural Networks
aamini/introtodeeplearning
Lab Materials for MIT 6.S191: Introduction to Deep Learning
remontoire-pac/ngc-dosdel
MATLAB code implementing cheminformatic and bioinformatic data analysis of DNA-encoded small-molecule library
salimamoukou/acv00
ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based models.
bp-kelley/descriptastorus
Descriptor computation(chemistry) and (optional) storage for machine learning
chemprop/chemprop
Message Passing Neural Networks for Molecule Property Prediction
CGATOxford/UMI-tools
Tools for handling Unique Molecular Identifiers in NGS data sets
totient-bio/deldenoiser
Remove effects of truncated side-products from read count data of a DNA-encoded library.
coleygroup/del_qsar
sourcery-ai/sourcery
Instant AI code reviews
google-deepmind/alphafold
Open source code for AlphaFold.
deepchem/deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
DeepGraphLearning/torchdrug
A powerful and flexible machine learning platform for drug discovery
kedro-org/kedro
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
google-deepmind/educational
csinva/imodels
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
faridrashidi/kaggle-solutions
🏅 Collection of Kaggle Solutions and Ideas 🏅
SeldonIO/alibi-detect
Algorithms for outlier, adversarial and drift detection
cjolowicz/hypermodern-python
Hypermodern Python
allegroai/clearml
ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
pbiecek/xai_resources
Interesting resources related to XAI (Explainable Artificial Intelligence)
pytorch/captum
Model interpretability and understanding for PyTorch
awjuliani/oreilly-rl-tutorial
Contains Jupyter notebooks associated with the "Deep Reinforcement Learning Tutorial" tutorial given at the O'Reilly 2017 NYC AI Conference.