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🤖 AI-Guru Projects

During my internship at AI Guru, Ahmedabad, I worked on hands-on AI and Machine Learning applications that go beyond tutorials. These projects reflect real problem-solving in computer vision — from building object detection pipelines to training custom deep learning models.

The highlight is the use of YOLOv8 (You Only Look Once, version 8) — a state-of-the-art real-time object detection model widely used in industry and research due to its speed and accuracy.

🔎 Projects

This repository contains four core projects built during my internship at AI Guru, Ahmedabad — each representing a different stage of my learning curve.


🤖 Training YOLO Models

A complete hands-on workflow for training custom object detection models using YOLO.

📓 Notebook:
https://github.com/Payal-mak/AI-Guru/blob/main/Train_YOLO_Models.ipynb

What this covers:

  • Understanding YOLO architecture and workflow
  • Preparing datasets in YOLO format
  • Training custom models
  • Evaluating performance
  • Running inference on new images

This project pushed me from using models to actually building and training them. It taught me how data, configuration, and compute come together to create intelligence.


📊 Indian Population Dashboard

A data-driven dashboard built using Streamlit, powered by real census data from the official Census of India website.

Highlights:

  • Uses authentic government datasets
  • Interactive visualizations for population trends
  • Filters by state, year, and demographic parameters
  • Focused on turning raw data into meaningful insight

This project taught me how real data behaves — messy, inconsistent, and full of edge cases — and how to design systems that still make sense of it.


📝 To-Do List App

My first React project, built to understand how modern frontend frameworks actually work.

What I explored:

  • Component-based architecture
  • State management
  • Event handling
  • Dynamic UI updates

Simple on the surface, but foundational in shaping how I think about frontend logic and user interaction.


🌦️ Weather App

A responsive web app that fetches and displays real-time weather data.

🛠️ Tech Stack

  • React JS
  • Vite
  • OpenWeatherMap API
  • CSS for styling

Features:

  • Search by city
  • Live temperature and conditions
  • Clean, minimal UI
  • API integration and error handling

This project pushed me to think beyond static pages and build applications that communicate with the real world.


🛠️ Technologies Used

Python — scripting and model implementation
YOLOv8 — object detection deep learning model ✔ Ultralytics — Python library for YOLO models
OpenCV — image/video processing
Jupyter Notebooks — experiment tracking and demonstration
Git & GitHub — version control and collaboration


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