Blog Posts
- Home /
- Blog Posts
Getting Started with MCP
What is MCP? MCP stands for Model Context Protocol. Think of it as a universal language that lets AI agents and models talk to each other, regardless of their underlying architecture or platform. Imagine you have a chatbot, a recommendation engine, and a document summarizer—all built with different frameworks. MCP acts as the bridge, making sure they can exchange information seamlessly.
Read More
Deploying Large Language Models Locally
Introduction We’ve all used AI chat models like ChatGPT, Gemini, and Claude in our daily lives. They’re great, but what happens when you want to integrate AI into your own applications? Most people turn to APIs—but there’s a catch.
Read More
Linear Regression using Gradient Descent Part-2
Introduction In this blog we are going to learn on how to implement Linear Regression using Gradient Descent using Python. We will not be directly using ML libraries like scikit-learn but instead do from scratch to increase our understanding. For representing the data we will be using NumPy library as it is efficient and we don’t need to waste our time creating a matrix library.
Read More
Linear Regression using Gradient Descent Part-1
Introduction Linear Regression is one of the simplest and most fundamental algorithms in Machine Learning and Statistics. It is used to model the relationship between a dependent variable (target) and one or more independent variables (features). The primary objective is to find the best-fitting line that minimizes the error between the actual and predicted values.
Read More