🏅 Best Data Science & ML

Open-source interactive computing notebook for data science and research.

Event-driven serverless compute on AWS — run code without managing servers.

Free cloud Jupyter notebooks with GPU/TPU access from Google.

Serverless JavaScript execution at the Cloudflare edge network globally.

Data science competition platform with free notebooks and datasets.

Serverless functions integrated with Vercel deployment and edge network.

AI model repository with 500k+ models and 150k+ datasets.

Deploy server-side code as AWS Lambda functions via Netlify CLI.

Google open-source ML framework for training and deploying models.

Event-driven serverless functions on Google Cloud infrastructure.

Facebook open-source ML framework favoured for research and LLMs.

Microsoft serverless compute with triggers, bindings, and Durable Functions.

Simple and efficient Python ML library for classical algorithms.

Open-source CLI for deploying serverless apps to AWS, Azure, and GCP.

Data analysis and manipulation library for Python.

Open-source framework for building full-stack serverless apps on AWS.

Fundamental package for scientific computing in Python.

AWS Serverless Application Model — framework for building Lambda applications.

Open-source serverless framework for AWS Lambda with infrastructure-as-code.

Open-source ML lifecycle management — tracking, models and registry.

Python serverless microframework for AWS Lambda from Amazon.

Deploy Python WSGI applications on AWS Lambda and API Gateway.

Open-source model serving and deployment framework.

AWS Lambda adapter for ASGI frameworks like FastAPI and Starlette.

Open-source distributed computing framework for ML and AI applications.

Infrastructure as code for serverless apps across any cloud provider.

Google managed ML platform for training, deploying and monitoring models.

JAMstack deployment platform with edge functions and global CDN.

AWS fully managed ML service for end-to-end model development.

Microsoft cloud ML service for building and deploying models at scale.