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. https://t.co/1kyhe4pwHHAvi Chawla (@_avichawla):Image scraping is finally here!Firecrawl’s latest v2 endpoint now lets you scrape visual content from the web to build multimodal LLM apps, fine-tune LLMs, and more.You can also apply specific filters like resolutions, aspect ratios, or image types.66k+ stars on GitHub! https://t.co/6uXa9am9ri ...

GitHub repo: https://t.co/EPrRn9rEdW(don't forget to star it ⭐ ) ...

Image scraping is finally here!Firecrawl’s latest v2 endpoint now lets you scrape visual content from the web to build multimodal LLM apps, fine-tune LLMs, and more.You can also apply specific filters like resolutions, aspect ratios, or image types.66k+ stars on GitHub! https://t.co/6uXa9am9ri ...

RT Avi Chawla (@_avichawla)You're in an ML Engineer interview at Microsoft.The interviewer asks:"Why Boosting models primarily use Trees as the base learner?What's wrong with Linear regression or SVMs?"You: "Because linear models can’t fit non-linear data."Interview over.Here's what you missed:Texts describing boosting start with “weak learners” but then immediately pivot to trees.But this DOES NOT mean they can only work with trees.Consider a simple boosting algorithm:1) Train a tree model.2) Calculate the ...

You're in an ML Engineer interview at Microsoft.The interviewer asks:"Why Boosting models primarily use Trees as the base learner?What's wrong with Linear regression or SVMs?"You: "Because linear models can’t fit non-linear data."Interview over.Here's what you missed:Texts describing boosting start with “weak learners” but then immediately pivot to trees.But this DOES NOT mean they can only work with trees.Consider a simple boosting algorithm:1) Train a tree model.2) Calculate the left-over residual.3) Trai ...

RT Avi Chawla (@_avichawla)First Principles Approach to MLOps!MadeWithML is the best place to learn how to combine AI/ML with software engineering to build production-grade solutions.These fundamentals are directly applicable to LLMOps as well.100% free and open-source. https://t.co/aqIbBTqIhg ...

GitHub repo: https://t.co/yvOusFBxel ...

First Principles Approach to MLOps!MadeWithML is the best place to learn how to combine AI/ML with software engineering to build production-grade solutions.These fundamentals are directly applicable to LLMOps as well.100% free and open-source. https://t.co/aqIbBTqIhg ...

Next, repeat these steps for the 2nd server to host the Smolagents Agent and its LLM.- Line 1-10 → Imports + define the Server & the LLM.- Line 12 → Decorate the method.- Line 21-28 → Define the Agent with a web search tool.- Line 31 → Serve the Agent.Finally, we use an ACP client to connect both agents in a workflow.- Line 6-7 → Connect the client to both servers.- Line 11-14 → Invoke the first agent to receive an output.- Line 18-21 → Pass the output to the next agent for enhancement.Next, run the two ser ...

ACP is a standardized, RESTful interface for Agents to discover and coordinate with other Agents, regardless of their framework.Just like A2A, it lets Agents communicate with Agents. There are some differences, which we shall discuss later.Here's how it works:- Build the Agents and host them on ACP servers.- The ACP server receives requests from the ACP Client and forwards them to the Agent.- ACP Client itself can be an Agent to intelligently route requests to the Agents (like MCP Client does).Let's dive in ...