TensorFlow, NumPy, Jupyter, Pandas, and PyTorch are the most popular tools in the category “Development & Training Tools”. “High Performance” is the primary reason developers pick TensorFlow over its competitors, while “Great for data analysis” is the reason why NumPy was chosen.
AI observability platform for ML and GenAI
Open-source, browser-local data exploration using DuckDB-WASM and PRQL
Improve the cost, performance, and accuracy of Gen AI apps
The platform for structured prompt engineering
Identify the root cause of problems in LLM apps
An open-source reactive notebook for Python
A deep learning library that simplifies training fast and accurate neural nets
Build production-grade data and ML pipelines
Turns data and AI algorithms into full web applications
Run any ML model from any programming language
A platform for collaborative data science and analytics
Train open-source ML models in minutes
Open-source ML observability and refinement tool
A truly statically typed Python notebook
A stream-batch unified feature store for real-time machine learning (By Alibaba)
A library for Transformers at scale (By Microsoft)
Data science at the speed of thought
The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data.