Popular GitHub Repositories for Java Json

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

?「AI 低代码平台」前后端分离 SpringBoot 2.x/3.x，SpringCloud，Ant Design&Vue3，Mybatis，Shiro！强大的代码生成器让前后端代码一键生成，无需写任何代码! 引领AI低代码开发模式 AI生成->OnlineCoding->代码生成->手工MERGE，帮助Java项目解决80%重复工作，让开发更关注业务，提高开发效率、节省成本，同时又不失灵活性

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node

Structured Text Generation

This is a collection of tutorials for learning how to use Docker with various tools. Contributions welcome.

AI Code Completions

CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.

Java version of LangChain

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

AI + Data, online. https://vespa.ai

Agentic AI Framework for Java Developers

The AI framework that adds the engineering to prompt engineering (Python/TS/Ruby/Java/C#/Rust/Go compatible)

JavaScript 对象的差异比较与修补

An Engine-Agnostic Deep Learning Framework in Java

百度NLP：分词，词性标注，命名实体识别，词重要性

ChatGPT Java SDK支持流式输出、Gpt插件、联网。支持OpenAI官方所有接口。ChatGPT的Java客户端。OpenAI GPT-3.5-Turb GPT-4 Api Client for Java

AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies