Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
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Turns Data and AI algorithms into production-ready web applications in no time.
An Open-Source Collection of Flash Cards to Help You Preparing Your Algorithms & Data Structures and System Design Interviews 💯
- algorithms
- data-structures
- array
- bit-manipulation
Simple and Distributed Machine Learning Python Library porting ML algorithms for 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.).
GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs
- apache-spark
- big-data
- connected-components
- dataframe
Data structure and algorithm library for go, designed to provide functions similar to C++ STL
oneAPI Data Analytics Library (oneDAL)
- onedal
- data-analysis
- oneapi
- machine-learning
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
- data-analytics
- data-cleaning
- data-cleansing
- data-engineering
A distributed Spark/Scala implementation of the isolation forest and extended isolation forest algorithms for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.
- isolation-forest
- spark
- outlier-detection
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
- svm
- regression
- classification
- machine-learning
Wisp CLI — Interactive trading platform for backtesting and live trading across spot, perpetual futures, options, and prediction markets
Implementation of Partitioning Around Medoids (PAM) in H2O-3
- clustering
- machine-learning
- h2o-3
- java