Linear Regression is one of the most fundamental algorithms in machine learning. In this post, we’ll implement it from scratch using JAX — Google’s high-performance numerical computing library that provides automatic differentiation and GPU/TPU acceleration.

A deep dive into JAX fundamentals, comparing it with PyTorch and TensorFlow, and understanding JIT compilation.

This blog post explains MCP Server and how to set it up using FastMCP. Additionally, it demonstrates how to create a simple AI Agent client that connects to the MCP server and utilizes the exposed tools.