Spark-And-MLlib-Projects

the portable Python dataframe library

Simple and Distributed Machine Learning

Apache Linkis builds a computation middleware layer to facilitate connection, governance and orchestration between the upper applications and the underlying data engines.

Implementing best practices for PySpark ETL jobs and applications.

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.

A curated list of awesome Apache Spark packages and resources.

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

Jupyter magics and kernels for working with remote Spark clusters

This is the github repo for Learning Spark: Lightning-Fast Data Analytics [2nd Edition]

Hopsworks - Data-Intensive AI platform with a Feature Store