That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):I just put together all my AI Agents posts in a single PDF.It covers:- Agent fundamentals- LLM vs RAG vs Agents- Agentic design patterns- Building Blocks of Agents- Building custom tools via MCP- 12 hands-on projects for AI EngineersDownload link in next tweet. https://t.co/LuQiyM5afF ...

That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Let's fine-tune OpenAI gpt-oss (100% locally): ...

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Evaluate conversational LLM apps like ChatGPT in 3 steps (open-source).Unlike single-turn tasks, conversations unfold over multiple messages.This means that the LLM's behavior must be consistent, compliant, and context-aware across turns, not just accurate in one-shot output. https://t.co/dugCyqQl6D ...

Technology & Development - Open-source tools enable building production-grade LLM web apps rapidly [1] - Interactive apps are more suitable for users focused on results rather than code [1] Data Science & Machine Learning - Data scientists and machine learning engineers commonly use Jupyter for data exploration and model building [1] - Tutorials and insights on DS, ML, LLMs, and RAGs are shared regularly [1]

General Overview - The document is a wrap-up and encourages sharing with the network [1] - It directs readers to Avi Chawla's profile for tutorials and insights on DS, ML, LLMs, and RAGs (Data Science, Machine Learning, Large Language Models, and Retrieval-Augmented Generation) [1] Focus Area - Avi Chawla's content includes explanations of Agentic AI systems [1]

Product Overview - MindsDB is presented as a federated query engine with a built-in MCP server [1] - The platform supports querying data from over 200 sources, including Slack, Gmail, and social platforms [1] - MindsDB offers query capabilities in both SQL and natural language [1] - The platform is 100% open-source and has over 33 thousand stars [1]

General Information - The content is a wrap-up and call to action to reshare the information [1] - The author shares tutorials and insights on Data Science (DS), Machine Learning (ML), Large Language Models (LLMs), and Retrieval Augmented Generation (RAGs) daily [1] Technical Focus - The author provides a clear explanation (with visuals) on how to sync GPUs in multi-GPU training [1]

Project Overview - The project involves building a mini-ChatGPT application [1] - The application is powered by DeepSeek-R1 and operates 100% locally [1] Resource Sharing - The author shares tutorials and insights on DS (Data Science), ML (Machine Learning), LLMs (Large Language Models), and RAGs (Retrieval-Augmented Generation) daily [1] - The author encourages readers to reshare the content with their network if they find it insightful [1]

General Information - This document is a recommendation to reshare insightful content related to Data Science (DS), Machine Learning (ML), Large Language Models (LLMs), and Retrieval Augmented Generation (RAGs) [1] - The document highlights 10 free GitHub repositories that can help individuals prepare for a career in AI engineering [1] Resources - The author, Avi Chawla (@_avichawla), shares tutorials and insights on DS, ML, LLMs, and RAGs daily [1]

If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Containerized versions of 450+ MCP servers in a single repo!- No manual setup—just pull the image.- Safe to run in isolated containers, unlike scripts.- Auto-updated daily.Easiest and safest way to use MCP servers with Agents. https://t.co/0dQAn8WBd7 ...