Popular GitHub Repositories for Polars Dataframe

Evidently is ??an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Statistical Machine Intelligence & Learning Engine

Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage

AI code-writing assistant that understands data content

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

A work in progress to build out solutions in Rust for MLOPs

Scripts and datasets for the O'Reilly book Python Polars: The Definitive Guide

Códigos Python com diferentes aplicações como técnicas de machine learning e deep learning, fundamentos de estatística, problemas de regressão de classificação. Os vídeos com as explicações teóricas estão disponíveis no meu canal do YouTube

2025-trading-automation-scripts

ML infrastructure for teams that just want to get sh*t done.

Build reliable AI and agentic applications with DataFrames

Use QLoRA to tune LLM in PyTorch-Lightning w/ Huggingface + MLflow

In-memory Graph Database and Knowledge Graph with Natural Language Interface, compatible with Pandas

FHIR to pandas dataframe for data analytics, AI and ML!

The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.

Java bindings for https://github.com/facebookincubator/velox