This repository provides a structured roadmap for learning Generative AI in 2024, targeting individuals looking to acquire foundational and advanced skills in the field. It offers a comprehensive learning path covering essential prerequisites, core concepts, and practical deployment strategies for Generative AI technologies.

How It Works

The roadmap is organized into distinct learning modules, starting with Python programming and progressing through basic Machine Learning and Deep Learning concepts. It then delves into advanced NLP techniques, including RNNs, LSTMs, and Transformers, before focusing on Generative AI models like GPT-4, Mistral, and LLaMA. The curriculum also covers vector databases (ChromaDB, FAISS, LanceDB) and deployment platforms (AWS, Azure, HuggingFace Spaces).

Quick Start & Requirements

• Prerequisites: Proficiency in Python, basic Machine Learning, and foundational Deep Learning concepts.
• Resources: Links to Python playlists (English/Hindi), Flask/FastAPI tutorials, and NLP/Deep Learning concept explanations are provided within the README.

Highlighted Details

• Covers a wide range of Generative AI models including GPT-4, Mistral 7B, LLaMA, and Google PaLM.
• Includes practical modules on vector databases like ChromaDB, FAISS, LanceDB, and Cassandra.
• Features deployment strategies using AWS, Azure, LangSmith, LangServe, and HuggingFace Spaces.
• Emphasizes advanced NLP concepts such as Attention mechanisms and Transformers.

Maintenance & Community

No specific information on contributors, sponsorships, or community channels is available in the provided README.

Licensing & Compatibility

The repository does not specify a license.

Limitations & Caveats

The roadmap is presented as a learning guide without accompanying code or pre-built tools, requiring users to implement or find separate resources for each step. The lack of a specified license may impact commercial use or integration into proprietary projects.