The Guide to LLM Evaluation Deci provides machine-learning models, research, training resources, or evaluation tools.
Directory
Search results
Published directory entries matching your search.
Vocal Remover uses AI for speech, voice, transcription, music, or other audio workflows.
LLM Agent, GenAI Agent, AI Service, Framework, Python, Chatbots, RAG, Agentic Framework.
Build AI agents and multi-agent workflows in.NET, Python, and Go with Microsoft Agent Framework.
neural frames uses AI to create, edit, transform, or animate video content.
Bleeding-Edge Multi-Agent Orchestration Framework for Enterprise Applications.
Apache Atlas – Data Governance and Metadata framework for Hadoop.
A library to compare Pandas, Polars, and Spark data frames. It provides stats and lets users adjust for match accuracy.
A lightweight framework for data analysis in JavaScript.
A fast, consistent tool for working with data frame like objects, both in memory and out of memory.
Framework that allows for the distributed processing of large data sets across clusters.
A tensor-based framework for large-scale data computation which is often regarded as a parallel and distributed version of NumPy.
Framework to create ChatGPT like bots over your dataset.
A python framework to transform natural language questions to queries in a database query language.
A Python Framework for Wind Energy Analysis and Prediction.
LlamaIndex is a data framework for your LLM applications.
A data framework for building LLM applications over external data.
The go-to, no-nonsense, fast and lean job site in AI, ML, Data Science and Big Data.
Scripts to generate a dataset with static frames from the Arcade Learning Environment.
A comparative framework for multimodal recommender systems with a focus on models leveraging auxiliary data.
A scalable general purpose micro-framework for defining dataflows.
SAMOA is a framework that includes distributed machine learning for data streams with an interface to plug-in different stream processing platforms.
A guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools.
The MIT AI Risk Initiative produces authoritative data and frameworks to help you identify, prioritize, and manage the risks from AI.