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AIML MINI PROJECTS

This repository features a curated collection of AI and ML-focused mini projects, ranging from foundational machine learning models to advanced NLP and computer vision applications.

📁 Projects Included

Project Name Description Tech Stack
AI Ping Pong A simple computer vs human ping-pong game. Python, Pygame
Population EDA Exploratory data analysis of demographic and population trends. Python, Pandas, Matplotlib
Titanic EDA Exploratory analysis of the Titanic dataset, including survival patterns and feature relationships. Python, Pandas, Seaborn
House Price Prediction Predicting house price based on area using linear regression. Python, Scikit-learn, Pandas
Salary Price Prediction Predicting salary based on experience using linear regression. Python, Scikit-learn, Pandas
Laptop Price Prediction Advanced data preprocessing and feature engineering for price estimation. Python, Scikit-learn, Seaborn
Startup Profit Prediction Predicting profit using multiple regression and categorical encoding. Python, Scikit-learn
Grocery List Categorizer Using Ollama (LLM) to intelligently categorize grocery items. Python, Ollama
Review-Sentiment-Analysis Sentiment analysis using MultinomialNB and CountVectorizer. Python, NLTK, Scikit-learn
Sales Data Analysis Descriptive data analysis with visualization. Python, Matplotlib, Seaborn
Iris REST API FastAPI-based REST API for flower species prediction. Fully dockerized. FastAPI, Docker, RandomForest
Data Patterns AI arXiv paper collector that searches, downloads PDFs, and indexes metadata matching "power distribution". Python, Selenium, Pandas, BeautifulSoup

🚀 Getting Started

1. Prerequisites

  • Python 3.8+
  • Ollama (Required for 'Grocery List Categorizer')
  • Docker (Optional, for 'Iris REST API')

2. Clone Repository

git clone https://github.com/Balaji-R-05/aiml-mini-projects.git
cd aiml-mini-projects

3. Setup Virtual Environment

python -m venv venv
# Windows
.\venv\Scripts\activate   
# Linux/MacOS
source venv/bin/activate

4. Install Dependencies

pip install -r requirements.txt

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