2024 Open source projects that are alternatives of or similar to Geni

Explore high-dimensional datasets and how your algo handles specific regions.

Ultimate Tennis Statistics and Tennis Crystal Ball - Tennis Big Data Analysis and Prediction

Alex Castrounis' curated set of resources for artificial intelligence (AI), machine learning, data science, internet of things (IoT), and more.

📝 A compilation of everything that I learn; Computer Science, Software Development, Engineering, Math, and Coding in General. Read the rendered results here ->

Quiz & Assignment of Coursera

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

Spark-Crawler: Apache Nutch-like crawler that runs on Apache Spark.

Essential Spark extensions and helper methods ✨😲

Thrill - An EXPERIMENTAL Algorithmic Distributed Big Data Batch Processing Framework in C++

A General-purpose Parallel and Heterogeneous Task Programming System

Geo Spatial Data Analytics on Spark

Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.

Read data from, write data to, and modify the formatting of Google Sheets

Advanced Pandas Vault — Utilities, Functions and Snippets (by @firmai).

Support content for my blog

Lightweight, general, scalable C++ library for finite element methods

An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset

Clean APIs for data cleaning. Python implementation of R package Janitor

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

An end-to-end GoodReads Data Pipeline for Building Data Lake, Data Warehouse and Analytics Platform.

Fill missing values in Pandas DataFrames using Restricted Boltzmann Machines

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

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

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

Javascript full-stack framework for Big Data visualisation and analysis

Robust, distributed version control for large files.

Python Helper library for Jupyter Notebooks

When Apache Pulsar meets Apache Spark

An open-source storage layer that brings scalable, ACID transactions to Apache Spark™ and big data workloads.

🎓 Jupyter notebooks from UFC data science course

VerticaPy is a Python library that exposes sci-kit like functionality to conduct data science projects on data stored in Vertica, thus taking advantage Vertica’s speed and built-in analytics and machine learning capabilities.

⛈️ Rumble 1.11.0 "Banyan Tree"🌳 for Apache Spark | Run queries on your large-scale, messy JSON-like data (JSON, text, CSV, Parquet, ROOT, AVRO, SVM...) | No install required (just a jar to download) | Declarative Machine Learning and more

Data science and Big Data with Python

📢 Ready to learn or review your knowledge!

Big Data for Data Engineers Coursera Specialization from Yandex

The Data Engineering Cookbook

Parallel Workflow extension for Rake, runs on multicores, clusters, clouds.

An R-focused pipeline toolkit for reproducibility and high-performance computing

Example end to end data engineering project.

A parallel application binary interface for Fortran 2018 compilers.

repo for code published on pythondata.com

Accelerate data science

Scalable stream processing platform for advanced realtime analytics on top of Kafka and Spark. LogIsland also supports MQTT and Kafka Streams (Flink being in the roadmap). The platform does complex event processing and is suitable for time series analysis. A large set of valuable ready to use processors, data sources and sinks are available.

A purely functional library to build distributed and event-driven systems

A Spark cluster setup running on Docker containers

Distributed Deep learning with Keras & Spark

Two-day workshop that covers how to use R to interact databases and Spark

Apache Spark on AWS Lambda

R on Apache Spark (SparkR) tutorials for Big Data analysis and Machine Learning as IPython / Jupyter notebooks

Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

A suite of benchmarks to test the sequential CPU and GPU performance of most popular high-performance libraries for Python.

Collaborate on privacy-preserving policy for data science projects in Pandas and Apache Spark

A tool for building feature stores.

🐍 Quick reference guide to common patterns & functions in PySpark.

Griffon Data Science Virtual Machine

Tools for computation on batch systems

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.).

Function-oriented Make-like declarative workflows for R

Python for Data Science (Seminar Course at UC Berkeley; AY 250)

Example workflows for the drake R package