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]

GitHub repo → https://t.co/Bsl7RYllmn ...

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 ...

A new ensemble technique that outperforms XGBoost, CatBoost, and LightGBM.Find the details in the explainer thread below: https://t.co/cgyg5Y4U2UAvi Chawla (@_avichawla):ML researchers just built a new ensemble technique.It even outperforms XGBoost, CatBoost, and LightGBM.Here's a complete breakdown (explained visually): ...

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):ML researchers just built a new ensemble technique.It even outperforms XGBoost, CatBoost, and LightGBM.Here's a complete breakdown (explained visually): ...

Here's the visual again for your reference:To recap, instead of training 32 (or K) separate MLPs, TabM uses one shared model and a lightweight adapter layer.Check this visual 👇 https://t.co/lF0yc2UjBb ...

ML researchers just built a new ensemble technique.It even outperforms XGBoost, CatBoost, and LightGBM.Here's a complete breakdown (explained visually): ...

9 real-world MCP projects for AI engineers that cover:- RAG- Memory- MCP client- Voice Agent- Agentic RAG- and much more!Find them in the explainer thread below. https://t.co/y4IAYWh54MAvi 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):A great tool to estimate how much VRAM your LLMs actually need.Alter the hardware config, quantization, etc., and get to know about:- Generation speed (tokens/sec)- Precise memory allocation- System throughput, etc.No more VRAM guessing! https://t.co/lZbIink12f ...

Try it here → https://t.co/cnIXhrJliZ ...