@nini_incrypto_: Want to learn AI system design? Just look at the real-world experience of top-tier companies! This amazing repository on GitHub aggregates over 500 real GenAI deployment cases from more than 130 big companies. It doesn't teach basic textbook theory but specifically breaks down the technical decisions of top teams in real production environments: 1. Uber: …
Summary
A repository on GitHub aggregates over 500 real GenAI deployment cases from more than 130 big companies, breaking down top teams' technical decisions in production environments, such as Uber's real-time traffic scheduling across multiple model providers.
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@wsl8297: When learning AI, the scariest part is getting stuck at "understanding the theory" and freezing when it's time to write code — not knowing where to start, and unable to find decent practice projects. I unearthed a practical treasure trove on GitHub: AI-Project-Gallery. It collects 30+ high-quality AI projects, covering classic topics like house price prediction and disease classification, as well as hot applications like Gemini chatbot and document generator...
This post shares a curated GitHub repository containing over 30 practical AI projects, covering domains from regression to generative AI, with many end-to-end examples, suitable for learners and developers.
@FakeMaidenMaker: Folks, we've dug up another AI engineering treasure: Hands-On-AI-Engineering. Just open-sourced, it already hit 2.3K stars. One repo stuffed with over 50 real AI projects that you can run directly. The most practical part is it doesn't talk about vague theories; each project is a complete little…
Recommends the freshly open-sourced GitHub repo Hands-On-AI-Engineering with 2.3K stars, containing over 50 runnable AI projects covering RAG, AI agent, OCR, and more. Each project provides full code and instructions, suitable for hands-on learning.
@Jolyne_AI: I found a solid hands-on tutorial for large language models on GitHub: the "Hands-On Large Model Series." It takes you from zero to mastering the entire tech stack. Using a combination of videos, documents, and code, it links key capabilities like fine-tuning, deployment, RAG, and Agent into a reproducible learning path — each knowledge point can be directly practiced...
Recommend the "Hands-on Large Model Series" tutorial on GitHub, which systematically explains practical techniques such as fine-tuning, deployment, RAG, and Agent through videos, documents, and code, suitable for AI developers to improve their engineering skills.
@nuannuan_share: If I wanted to land a $200K AI engineer job in 90 days, I wouldn't go back to school. I'd master these 10 GitHub repositories. 1. awesome-llm-apps — A production-grade AI guide covering RAG, agents, and multimodal apps with full code. 106K+ stars. Repo …
A Chinese social media post recommends 10 GitHub repositories, claiming that mastering them can help land a $200K AI engineer job within 90 days. The repos cover mainstream AI development frameworks and tools including LangChain, LangGraph, CrewAI, Ollama, and Qdrant.
@IndieDevHailey: This might be the hardest-core open-source AI engineering course on the internet. The GitHub trending project: ai-engineering-from-scratch has already gained 17.4k+ Stars. It's not another AI tutorial that teaches you how to call APIs; instead, it truly guides you to build AI systems from scratch.
Introduces the trending open-source AI engineering course project ai-engineering-from-scratch on GitHub, which has earned 17.4k+ Stars. It offers 435 lessons across 20 stages, covering mathematical principles to hand-built AI systems, supports multiple languages, and aims to help learners deeply understand the underlying principles of AI.