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]

Technology & Software Deployment - Containerized versions of 450+ MCP servers are available in a single repository [1] - The solution offers an easy and safe way to use MCP servers with Agents [1] - No manual setup is required; users can simply pull the image [1] - The solution is safe to run in isolated containers, unlike scripts [1] - The solution is auto-updated 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):9 MCP projects for AI engineers (with code): ...

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):Trace and evaluate any AI/LLM app in 3 lines of code!- Initialize an eval with LangWatch (line 3)- Decorate the LLM workflow method (line 5)- Log the evaluation (line 11)You can keep using Pandas and your other favorite tools.100% open-source! https://t.co/J7dxnMmKdC ...

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):Train AI models on data that does not even exist!SDV is an open-source framework that uses ML to learn patterns from your real data and generate tabular synthetic data at scale.Supports built-in anonymization, validation, and more. https://t.co/KyTZsaILvh ...