This project is about predicting the success of movies using machine learning. The model is trained on a large dataset of movies to identify patterns and make accurate predictions about a movie's potential success based on various features.
GitHub repository with 5 stars and 0 forks.
Language: Jupyter Notebook
Trending score 0.06, freshness score 0.28, stars gained +0, forks gained +0.
2026-07-15: 5 stars and 0 forks.
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
GitHub repository with 31,293 stars and 3,054 forks.
Trending score: 4.38; stars gained: +347; forks gained: +28.
Language: Jupyter Notebook
Topics: chatglm, chatglm3, gemma-2b-it, glm-4, internlm2, llama3
21 Lessons, Get Started Building with Generative AI
GitHub repository with 113,009 stars and 60,715 forks.
Trending score: 3.79; stars gained: +58; forks gained: +32.
Language: Jupyter Notebook
Topics: ai, chatgpt, dall-e, generativeai, gpt, azure
Learn about the fundamentals of LangGraph through a series of notebooks
GitHub repository with 517 stars and 123 forks.
Trending score: 2.45; stars gained: +25; forks gained: +4.
Language: Jupyter Notebook
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
GitHub repository with 16,756 stars and 5,465 forks.
Trending score: 2.40; stars gained: +11; forks gained: +1.
Language: Jupyter Notebook
Topics: csharp, java, javascript, mcp, mcp-client, mcp-security
Developer Asset Hub for NVIDIA Nemotron — A one-stop resource for training recipes, usage cookbooks, datasets, and full end-to-end reference examples to build with Nemotron models
GitHub repository with 1,695 stars and 346 forks.
Trending score: 2.32; stars gained: +8; forks gained: +2.
Language: Jupyter Notebook
Topics: ai, fine-tuning, model-training, nemotron, nvidia, reinforcement-learning
Optimize prompts, code, and more with AI-powered Reflective Text Evolution
GitHub repository with 5,653 stars and 464 forks.
Trending score: 2.27; stars gained: +7; forks gained: +1.
Language: Jupyter Notebook
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
GitHub repository with 31,293 stars and 3,054 forks.
Trending score: 4.38; stars gained: +347; forks gained: +28.
Language: Jupyter Notebook
Topics: chatglm, chatglm3, gemma-2b-it, glm-4, internlm2, llama3
21 Lessons, Get Started Building with Generative AI
GitHub repository with 113,009 stars and 60,715 forks.
Trending score: 3.79; stars gained: +58; forks gained: +32.
Language: Jupyter Notebook
Topics: ai, chatgpt, dall-e, generativeai, gpt, azure
Learn about the fundamentals of LangGraph through a series of notebooks
GitHub repository with 517 stars and 123 forks.
Trending score: 2.45; stars gained: +25; forks gained: +4.
Language: Jupyter Notebook
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
GitHub repository with 16,756 stars and 5,465 forks.
Trending score: 2.40; stars gained: +11; forks gained: +1.
Language: Jupyter Notebook
Topics: csharp, java, javascript, mcp, mcp-client, mcp-security
Developer Asset Hub for NVIDIA Nemotron — A one-stop resource for training recipes, usage cookbooks, datasets, and full end-to-end reference examples to build with Nemotron models
GitHub repository with 1,695 stars and 346 forks.
Trending score: 2.32; stars gained: +8; forks gained: +2.
Language: Jupyter Notebook
Topics: ai, fine-tuning, model-training, nemotron, nvidia, reinforcement-learning
Optimize prompts, code, and more with AI-powered Reflective Text Evolution
GitHub repository with 5,653 stars and 464 forks.
Trending score: 2.27; stars gained: +7; forks gained: +1.
Language: Jupyter Notebook