SZegota's Stars
microsoft/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
KindXiaoming/pykan
Kolmogorov Arnold Networks
zhanymkanov/fastapi-best-practices
FastAPI Best Practices and Conventions we used at our startup
tracel-ai/burn
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
sktime/sktime
A unified framework for machine learning with time series
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
grf-labs/grf
Generalized Random Forests
Oxen-AI/oxen-release
Lightning fast data version control system for structured and unstructured machine learning datasets. We aim to make versioning datasets as easy as versioning code.
numerai/example-scripts
A collection of scripts and notebooks to help you get started quickly.
Appsilon/shiny.fluent
Microsoft's Fluent UI for Shiny apps
mwelz/GenericML
R implementation of Generic Machine Learning Inference (Chernozhukov, Demirer, Duflo and Fernández-Val, 2020).
ahaeusser/echos
Echo State Networks for Time Series Forecasting