H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

A simple Spark-powered ETL framework that just works 🍺

A Clojure dataframe library that runs on Spark

Koalas: pandas API on Apache Spark

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL [email protected]

Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines.

Apache Spark - A unified analytics engine for large-scale data processing

Apache Spark 官方文档中文版

Verteego Data Suite

Javascript full-stack framework for Big Data visualisation and analysis

A heterogeneous Apache Spark framework.

Efficient variant-call data storage and retrieval library using the TileDB storage library.

Python Helper library for Jupyter Notebooks

Sparkling Water provides H2O functionality inside Spark cluster

🚚 Agile Data Preparation Workflows made easy with dask, cudf, dask_cudf and pyspark

Word2Vec models with Twitter data using Spark. Blog:

When Apache Pulsar meets Apache Spark