the portable Python dataframe library

Simple and Distributed Machine Learning

State of the Art Natural Language Processing

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

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.

Implementing best practices for PySpark ETL jobs and applications.

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

🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark

Jupyter magics and kernels for working with remote Spark clusters

SQL data analysis & visualization projects using MySQL, PostgreSQL, SQLite, Tableau, Apache Spark and pySpark.

PySpark-Tutorial provides basic algorithms using PySpark

Hopsworks - Data-Intensive AI platform with a Feature Store

MapReduce, Spark, Java, and Scala for Data Algorithms Book

Sparkling Water provides H2O functionality inside Spark cluster

Scriptis is for interactive data analysis with script development(SQL, Pyspark, HiveQL), task submission(Spark, Hive), UDF, function, resource management and intelligent diagnosis.

Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such as Airbyte, dbt, or Great Expectations together in one intuitive interface built with React Flow. In addition we provide third-party data into data sc…

pyspark🍒🥭 is delicious，just eat it!😋😋

80+ DevOps & Data CLI Tools - AWS, GCP, GCF Python Cloud Functions, Log Anonymizer, Spark, Hadoop, HBase, Hive, Impala, Linux, Docker, Spark Data Converters & Validators (Avro/Parquet/JSON/CSV/INI/XML/YAML), Travis CI, AWS CloudFormation, Elasticsearch, Solr etc.

A comprehensive Spark guide collated from multiple sources that can be referred to learn more about Spark or as an interview refresher.