Modin: Scale your Pandas workflows by changing a single line of code

pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

Lightweight and extensible compatibility layer between dataframe libraries!

Distributed XGBoost on Ray

Python and Pandas are known to have issues around scalability and efficiency. You will learn how to use libraries such as Modin, Dask, Ray, Vaex etc to overcome the problems faced by Pandas.

A low-level execution library for analytic data processing.

A Kedro plugin that provides pandas dropin replacements for the pandas datasets (e.g modin and cuDF)

Unlimited Data-Science Benchmarks for Numeric, Tabular and Graph Workloads

Open Data Profiling, Quality and Analysis on NYC OpenData dataset with semantic profiling using fuzzy ratio, Levenshtein distance and regex

oneAPI Hackathon: The LLM Challenge

Simple example on how Modin can peed up your Pandas workflows by changing a single line of code

AI Starter Kit to generate structured synthetic data using Intel® Distribution of Modin

HHA507 / Data Science / Assignment 2 / Data Manipulation

Generate data, load and download parquets to GCP and compare performance between Pandas, Polars and Modin with Python

Using the MovieLens dataset with Surprise to compare different algorithms for rating prediction, and also create a movie recommendation system on top of it.

A transformation pipeline for Delta Lake using AWS SDK for Pandas

Recommendation system approaches

Global Markets Options Pricing