Popular GitHub Repositories for Pyspark

Simple and Distributed Machine Learning

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

Hopsworks - Data-Intensive AI platform with a Feature Store

A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models

MorphL Community Edition uses big data and machine learning to predict user behaviors in digital products and services with the end goal of increasing KPIs (click-through rates, conversion rates, etc.) through personalization

Isolation Forest on Spark

Toolkit for Apache Spark ML for Feature clean-up, feature Importance calculation suite, Information Gain selection, Distributed SMOTE, Model selection and training, Hyper parameter optimization and selection, Model interprability.

Relation Extraction using Deep learning(CNN)

Spark 2.0 Python Machine Learning examples

This repository provides a comprehensive implementation of a deep neural network-based recommendation system similar to YouTube's. The repo is organized to include the core Python implementation of the model and a Spark-based Scala solution for data generation and model serving.

《 Python机器学习及实践：从零开始通往Kaggle竞赛之路（2022年度版）》全书数据和开源代码

Pyspark in Google Colab: A simple machine learning (Linear Regression) model

Finding customer lookalikes using Machine Learning in PySpark

Streamlit example showing Scikit Learn & Pyspark ML over Healthcare data ! Its simple !!

Code and links to the data for the article "Machine Learning Pipelines with Modern Big DataTools for High Energy Physics"

PyPi module for Graphlet AI Knowledge Graph Factory

ESG-investment AI

My presentation at ODSC India 2018 about Deep Learning with Apache Spark

《 Python人工智能编程实践（2024年度版）》全书数据和开源代码