๐ Why Original Work Matters in Your Final Year Project (And How It Can Shape Your Career)
In engineering colleges across the country, final year projects are often treated as just another academic task. But what many students fail to realize is this: Your final year project isnโt just a submission. Itโs your first real-world proof of work. And thatโs exactly why original work in your final…
๐ How to Choose Your Final Year Project: A Practical Guide for BTech Students
Choosing the right final year project is one of the most important decisions of your engineering journey. Itโs more than just a submission โ itโs a reflection of your interests, skills, and future goals. Unfortunately, many students pick projects based on what their friends are doing or whatโs available last…
๐ง MCP Server: Model Context Prototyping with Gemini + MySQL + FastAPI
GitHub: https://github.com/nishantmunjal2003/mcp-server-gemini ๐ Project Overview MCP Server is a lightweight, extendable API server that: โ๏ธ Features ๐ Folder Structure bashCopyEditmcp-server/ โ โโโ app.py # Main FastAPI server โโโ gemini_integration.py # Gemini API integration โโโ schema.sql # SQL for DB setup โโโ requirements.txt # Python dependencies โโโ .env # Environment variables…
Prompts for Image Descriptions
Describe the scene using three vivid sensory details โ one for sight, one for sound, and one for touch. Summarize the mood of the image in one powerful sentence without naming any objects. Write a poetic description of the image focusing only on colors and emotions. Imagine the main subject…
Dimensionality Reduction
Dimensionality reduction is the process of reducing the number of features (variables) in a dataset while preserving important information. It helps in: โ Reducing computational cost (faster processing)โ Removing noise from dataโ Avoiding overfittingโ Visualizing high-dimensional data Types of Dimensionality Reduction 1. Feature Selection (Selecting important features) 2. Feature Extraction…
Why Initialize Weights in Neural Network
Initializing weights and biases is a crucial step in building a neural network. Proper initialization helps ensure that the network converges to a good solution and does so efficiently. Let’s explore the reasons in detail: 1. Breaking Symmetry If all weights are initialized to the same value (e.g., zeros), then…