Popular GitHub Repositories for Analytics

A collection of libraries to optimise AI model performances

? ? ? ? GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统

SQL reporting that Just Works. Fast, simple, and confusion-free. Write and share queries in a delightful SQL editor, with AI assistance.

? Monitor deep learning model training and hardware usage from your mobile phone ?

Analysis, Comparison, Trends, Rankings of Open Source Software, you can also get insight from more than 7 billion with natural language (powered by OpenAI). Follow us on Twitter: https://twitter.com/ossinsight

Easy token price estimates for 400+ LLMs. TokenOps.

Metering and Billing for AI, API and DevOps. Collect and aggregate millions of usage events in real-time and enable usage-based billing.

The ultimate LLM Ops platform - Monitoring, Analytics, Evaluations, Datasets and Prompt Optimization ?

Powerful Analytics Solution. Setup in 30 seconds. Display all your data on a Simple, AI-powered dashboard. Fully self-hostable and GDPR compliant. Alternative to Google Analytics, MixPanel, Plausible, Umami & Matomo.

AI-powered Jupyter Notebook — use local AI to generate and edit code cells, automatically fix errors, and chat with your data

Career Resources for Data Science, Machine Learning, Big Data and Business Analytics Career Repository

do more with dbt. dbt-fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.

AI projects

LexNLP by LexPredict

Data API Framework for AI Agents and Data Apps

oneAPI Data Analytics Library (oneDAL)

one sentence generates any graph

Universal AI Agent Frontend. Build your backend we handle the rest.

ML-capsule is a Project for beginners and experienced data science Enthusiasts who don't have a mentor or guidance and wish to learn Machine learning. Using our repo they can learn ML, DL, and many related technologies with different real-world projects and become Interview ready.

Text analytics for LLM apps. Cluster messages to detect use cases, outliers, power users. Detect intents and run evals with LLM (OpenAI, MistralAI, Ollama, etc.)