- London, UK
- @KishManani
Stars
Streamlit โ A faster way to build and share data apps.
Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
A light-weight, flexible, and expressive statistical data testing library
PySpark test helper methods with beautiful error messages
๐ ๐ง๐ต๐ฒ ๐๐๐น๐น ๐ฆ๐๐ฎ๐ฐ๐ธ ๐ณ-๐ฆ๐๐ฒ๐ฝ๐ ๐ ๐๐ข๐ฝ๐ ๐๐ฟ๐ฎ๐บ๐ฒ๐๐ผ๐ฟ๐ธ | ๐๐ฒ๐ฎ๐ฟ๐ป ๐ ๐๐ & ๐ ๐๐ข๐ฝ๐ for free by designing, building and deploying an end-to-end ML batch system ~ ๐ด๐ฐ๐ถ๐ณ๐ค๐ฆ ๐ค๐ฐ๐ฅ๐ฆ + 2.5 ๐ฉ๐ฐ๐ถ๐ณ๐ด ๐ฐ๐ง ๐ณ๐ฆ๐ข๐ฅ๐ช๐ฏ๐จ & ๐ท๐ช๐ฅ๐ฆ๐ฐ ๐ฎ๐ข๐ต๐ฆ๐ณ๐ช๐ข๐ญ๐ด
Data for and description of the ACIC 2023 data competition
KishManani / sktime
Forked from sktime/sktimeA unified framework for machine learning with time series
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
GOV.UK staff use this repository as a forum to discuss and make technical decisions
Auto-Editor: Efficient media analysis and rendering
A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
A repo with a minimal Sphinx example for Python documentation.
Run ruff, isort, pyupgrade, mypy, pylint, flake8, and more on Jupyter Notebooks
A plugin for Flake8 finding likely bugs and design problems in your program. Contains warnings that don't belong in pyflakes and pycodestyle.
A unified framework for machine learning with time series
A validation library for Pandas data frames using user-friendly schemas
Feature engineering package with sklearn like functionality
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
A game theoretic approach to explain the output of any machine learning model.
A C++ platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
Slides and notebooks for my tutorial at PyData London 2018