1. “Quick Start Guide to Large Language Models”: Provides practical guidance on working with and deploying LLMs such as GPT-4, BERT, T5, and LLaMA to solve real-world problems, including sample codes.
2. “Introduction to Generative AI”: Covers the fundamentals of generative AI and how to use it safely and effectively in personal and professional workflows.
3. “Generative AI with LangChain”: A guide to using the LangChain framework to develop and deploy production-ready LLM applications, including prompt engineering to improve performance.
4. “LangChain Crash Course”: Covers the fundamentals of LangChain and teaches how to build LLM-powered applications using hands-on exercises.
5. “LangChain in your Pocket”: A guide to creating powerful applications using LLMs, covering topics like Auto-SQL, NER, RAG, and Autonomous AI agents with step-by-step code explanations.
6. “Generative AI on AWS”: Covers the entire generative AI project lifecycle on Amazon Bedrock, including using LangChain to develop agents and actions.
7. “Machine Learning Engineering with Python”: A comprehensive guide to building and scaling machine-learning projects, including a section on generative AI and building LLM-powered pipelines using LangChain.
8. “Developing Apps With GPT-4 and ChatGPT”: Teaches how to create applications with large language models, covering topics like prompt engineering, model fine-tuning, and frameworks like LangChain.
9. “LangChain Handbook”: A complete guide to integrating and implementing LLMs using the LangChain framework, covering applications like chatbots, document analysis, and code analysis.
10. “LangChain for Everyone”: Covers the practical ways the LangChain framework can be leveraged to develop LLM-powered applications in various industries.
For more information and free consultation, you can reach out to AI Lab in Telegram @aiscrumbot or follow @itinaicom on Twitter.
