MLE-bench is a benchmark for measuring how well AI agents perform at machine learning engineering

Source code of DRAGIN, ACL 2024 main conference Long Paper

Jobs_Applier_AI_Agent_AIHawk aims to easy job hunt process by automating the job application process. Utilizing artificial intelligence, it enables users to apply for multiple jobs in a tailored way.

Build resilient language agents as graphs.

This is a repo with links to everything you'd ever want to learn about data engineering

NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference i…

A super fast Graph Database uses GraphBLAS under the hood for its sparse adjacency matrix graph representation. Our goal is to provide the best Knowledge Graph for LLM (GraphRAG).

Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.

Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…

Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

A curation of awesome portfolio website ideas for developers and designers to draw inspiration from. Raise a pull request to add more. 💜

This repo contains the reference implementation for the Microsoft Learn Azure OpenAI end to end chat baseline.

Inference code for Llama models

Deep Reinforcement Learning: Zero to Hero!

Set of tools to assess and improve LLM security.

An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).

The official Meta Llama 3 GitHub site

Web scrapping and related analytics using Python tools

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Learn how to design, develop, deploy and iterate on production-grade ML applications.

ZenML 🙏: The bridge between ML and Ops. https://zenml.io.

MLOps using Azure ML Services and Azure DevOps

MLOps examples

Source code of the Apache Airflow Tutorial for Beginners on YouTube Channel Coder2j (https://www.youtube.com/c/coder2j)

💯 Curated coding interview preparation materials for busy software engineers