azeygr

azeygr's Stars

• fishaudio/fish-speech

  Brand new TTS solution

  Language:Python13.8k1k

• OverLordGoldDragon/ssqueezepy

  Synchrosqueezing, wavelet transforms, and time-frequency analysis in Python

  Language:Python64396

• awslabs/python-deequ

  Python API for Deequ

  Language:Jupyter Notebook723135

• FreeOpcUa/opcua-asyncio

  OPC UA library for python >= 3.7

  Language:Python1.1k362

• faust-streaming/faust

  Python Stream Processing. A Faust fork

  Language:Python1.6k183

• robinhood/faust

  Python Stream Processing

  Language:Python6.7k533

• sqlfluff/sqlfluff

  A modular SQL linter and auto-formatter with support for multiple dialects and templated code.

  Language:Python7.9k725

• h2non/jsonpath-ng

  Finally, a JSONPath implementation for Python that aims to be standard compliant. That's all. Enjoy!

  Language:Python60487

• Azure-Samples/iot-edge-proficy-historian

  C# Proficy Historian Module for Azure IoT Edge

  Language:C#114

• br3ndonland/template-python

  Template repository for Python projects

  Language:Python327

• pre-commit/pre-commit-hooks

  Some out-of-the-box hooks for pre-commit

  Language:Python5.3k705

• contiamo/rhombic

  SQL parsing, lineage extraction and manipulation

  Language:TypeScript468

• tokern/data-lineage

  Generate and Visualize Data Lineage from query history

  Language:Python31145

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Language:C++6.3k729

• google/lightweight_mmm

  LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

  Language:Python883189

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook22.8k3.3k

• rapidsai/cudf

  cuDF - GPU DataFrame Library

  Language:C++8.4k900

• rapidsai/cuxfilter

  GPU accelerated cross filtering with cuDF.

  Language:Python27768