Apache Spark - A unified analytics engine for large-scale data processing
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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.
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
List of Data Science Cheatsheets to rule the world
GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.
Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
Python SQL Parser and Transpiler
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.
macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
Koalas: pandas API on Apache Spark
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.).
Distributed Deep learning with Keras & Spark
MLeap: Deploy ML Pipelines to Production
:truck: 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
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
The Archives Unleashed Toolkit is an open-source toolkit for analyzing web archives.
Formal specification and generation of verifiable binary parsers, message generators and protocol state machines
Helpers & syntactic sugar for PySpark.
Various examples of notebooks for working with web archives with the Archives Unleashed Toolkit, and derivatives generated by the Archives Unleashed Toolkit.