{"repo":"Ramakm/ai-hands-on","free":true,"listed":false,"github":"https://github.com/Ramakm/ai-hands-on","clone":"git clone https://github.com/Ramakm/ai-hands-on.git","description":"A group of notebooks and other files which can help you learn AI from scratch.","language":"Jupyter Notebook","stars":1322,"topics":["ai","artificial-intelligence","books","chatbot","machine-learning","math","ml","mlmodel","neural-network","ocr"],"license":"MIT","category":"machine-learning","readme_excerpt":"AI Engineering: Hands-on A complete, hands-on guide to becoming an AI Engineer. This repository is designed to help you learn AI from first principles, build real neural networks, and understand modern LLM systems end-to-end. You'll progress through math, PyTorch, deep learning, transformers, RAG, and OCR — with clean, intuitive Jupyter notebooks guiding you at every step. Whether you're a beginner or an engineer levelling up, this repo gives you the clarity, structure, and intuition needed to build real AI systems. ⭐ Star This Repo If you learn something useful, a star is appreciated. Repository Structure 1. Math Fundamentals - Math functions, derivatives, vectors, and gradients - Matrix operations and linear algebra - Probability and statistics 2. PyTorch Basics - Creating and manipulating tensors - Matrix multiplication, transposing, and reshaping - Indexing, slicing, and concatenating tensors - Special tensor creation functions 3. Neural-Network(NN) - Building neurons, layers, and networks from scratch - Normalization techniques (RMSNorm) - Activation functions - Optimizers (Adam, Muon) and learning rate decay 4. Transformers - Attention and self-attention mechanisms - Multi-head attention - Decoder-only transformer architecture 5. Retrieval-Augmented Generation (RAG) - Building RAG pipelines end to end - Indexing, retrieval, chunking strategies - Integrations with embedding models and vector stores - Cloud LLM support: Atlas Cloud ( deepseek-ai/DeepSeek-V3-0324 by defaul","default_branch":null,"files":null,"tree":[],"storefront":"/r/Ramakm","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Ramakm/ai-hands-on/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}