A complete, modern, developer-focused handbook for mastering Claude Code, Vibe Coding techniques, AI-powered workflows, project planning with PLAN.md & PROGRESS.md, and intelligent agent-driven development.

This is a repository accompanying the survey Edge AI Meets LLM (coming soon), containing a comprehensive list of papers, codebases, toolchains, and open-source frameworks. It is intended to serve as a handbook for researchers and developers interested in Edge/Mobile LLMs.

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Best Cursor AI prompts by programming language + basic usage guide. A practical handbook for Cursor AI: basics, workflows, and prompt examples. Curated Cursor AI prompt library for developers (multi-language). Cursor AI guide with prompt templates for coding and debugging. Cursor AI prompts collection + beginner-friendly documentation.

This is a full stack web application that uses data scraped from the UTS handbook to recommend subjects using an AI that takes data from the past subjects a student has taken and a personality quiz. It was developed using Angular, Node.js, Python (with Flask and Scikit) and MySQL hosted on AWS (Amplify, API Gateway, Lambda, RDS and EC2). This was a project I developed in a team of people and I was a full stack developer (developed almost the entire backend).

A comprehensive college-level textbook on AI-powered development

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A reference for AI Driven Development

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A structured, practical guide for developers to learn AI/ML from fundamentals to production-ready systems.

Build AI-Powered Flutter Apps — A Developer's Handbook. Complete source code for the book.

A practical, developer-first handbook for structuring React + FastAPI projects—from AI MVPs to scalable platforms.

From Prompt to Production: The AI Developer's Rapid Workflow An interactive handbook for BS Computer Science students, prepared by Mr. Haseeb.

தமிழ் AI கட்டளை வடிவமைப்பு கையேடு — Open-source Tamil Prompt Engineering Handbook with 200+ ready-to-use prompt templates across 10+ roles (developers, poets, marketers, educators & more). Frameworks: CLEAR, CRAFT, AUTOMAT, CATS.

This project turns messy GitHub documentation into a clean, readable onboarding handbook. Using Python, OpenAI, Streamlit, and a .NET + IronPDF backend, it automatically pulls Markdown files from a repo, summarizes them with AI, and generates a polished PDF that new developers can actually read from start to finish.

I am designing this repository for the developers, machine learning engineers and AI practioners to excel in the deployment and the operational management of the LLMs . Whether you are developinmg custom LLM solution or finetuning the pre-trained model, this handbook will help you with the tools, resources and workflow needed to bring LLMs to prod.