thuijskens's Stars
mckinsey/causalnex
A Python library that helps data scientists to infer causation rather than observing correlation.
ucbrise/hypersched
Deadline-based hyperparameter tuning on RayTune.
ray-project/ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
plasma-umass/scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
uber/manifold
A model-agnostic visual debugging tool for machine learning
TDAmeritrade/stumpy
STUMPY is a powerful and scalable Python library for modern time series analysis
streamlit/streamlit
Streamlit — A faster way to build and share data apps.
sktime/sktime
A unified framework for machine learning with time series
alan-turing-institute/rse-course
Materials for The Alan Turing Institute's Research Software Engineering course
WinVector/pyvtreat
vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distributed under a BSD-3-Clause license.
jmschrei/apricot
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html
flytxtds/AutoGBT
AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-drift. AutoGBT was developed by a joint team ('autodidact.ai') from Flytxt, Indian Institute of Technology Delhi and CSIR-CEERI as a part of NIPS 2018 AutoML for Lifelong Machine Learning Challenge.
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.
online-ml/river
🌊 Online machine learning in Python
rtqichen/torchdiffeq
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
HunterMcGushion/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
MLBazaar/BTB
A simple, extensible library for developing AutoML systems
civisanalytics/civisml-extensions
scikit-learn-compatible estimators from Civis Analytics
ikatsov/tensor-house
A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.
victoresque/pytorch-template
PyTorch deep learning projects made easy.
scikit-learn-contrib/skope-rules
machine learning with logical rules in Python
scikit-garden/scikit-garden
A garden for scikit-learn compatible trees
sramirez/fast-mRMR
An improved implementation of the classical feature selection method: minimum Redundancy and Maximum Relevance (mRMR).
FilippoBovo/production-data-science
Production Data Science: a workflow for collaborative data science aimed at production
DistrictDataLabs/yellowbrick
Visual analysis and diagnostic tools to facilitate machine learning model selection.
shap/shap
A game theoretic approach to explain the output of any machine learning model.
donlnz/nonconformist
Python implementation of the conformal prediction framework.
MLWave/Kaggle-Ensemble-Guide
Code for the Kaggle Ensembling Guide Article on MLWave