Popular GitHub Repositories for Analyzing Patterns

This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.

Build effective agents using Model Context Protocol and simple workflow patterns

A Python scikit for building and analyzing recommender systems

An open source framework for building AI-powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit works with various models and platforms.

RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.

State-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc.

A Model Context Protocol server for searching and analyzing arXiv papers

Convolutional neural network for analyzing pentest screenshots

?A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc

Social media (Weibo) comments analyzing toolbox in Chinese 微博评论分析工具, 实现功能: 1.微博评论数据爬取; 2.分词与关键词提取; 3.词云与词频统计; 4.情感分析; 5.主题聚类

Exploiting Bitcoin prices patterns with Deep Learning.

AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.

Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo

AI Chatbot for analyzing/extracting information from data in conversational format.

APO is a one-stop observability platform combining OpenTelemetry with eBPF. Leveraging LLM capabilities to enable auto-pilot analyzing and troubleshooting ?.

This is a repository with the code for the ACL 2019 paper "Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned" and the ACL 2021 paper "Analyzing Source and Target Contributions to NMT Predictions".

A community-driven knowledge base of practical patterns for Effect-TS.

A package for parsing PDFs and analyzing their content using LLMs.

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

A comprehensive collection of AI development patterns for building software with AI assistance, organized by implementation maturity and development lifecycle phases. Includes Foundation, Development, and Operations patterns with practical examples and anti-patterns.