Ideathon

Overview

This repository is a collection of data science and AI experiments, featuring a complete Machine Learning pipeline for Walmart stock price prediction. It covers data cleaning, building and training an ML model, and deploying evaluation scripts. Future goals include adding an AI chatbot to further enrich interactive capabilities.

Key Features

• Walmart Stock Price Prediction Model: End-to-end process from raw data to deployed ML model.
  • Data cleaning and preprocessing (remove nulls, encoding, normalization).
  • Feature engineering for improved forecasting accuracy.
  • Model training and validation (Regression/Classification models).
  • Evaluation using metrics like RMSE, MAE, etc.
• User Authentication System: Secure logins for application flows.
• Preprocessing Tools: Ready-to-use encoders for categorical data (cities, products).
• Ready-to-use Notebooks: Jupyter Notebooks for demo, exploration, and reports.

Technologies Used

• Python, Jupyter Notebook
• pandas, numpy, matplotlib, scikit-learn
• Pickle (for model serialization)
• ML Algorithms (e.g., Linear Regression, RandomForest, etc.)

Planned Models

• AI Chatbot: To be added soon for interactive user experience, customer support, and automation.

Project Structure

• .ipynb_checkpoints/ : Notebook autosaves
• __pycache__/ : Python cache files
• *.csv : Walmart stock and other datasets
• app.py, auth.py : Main application and authentication logic
• help_demo.py, new.py: Supporting scripts
• *.pkl : Pre-trained encoder and ML model files
• Untitled.ipynb : Demonstration and report notebook

Getting Started

1. Clone the repo:
2. Explore Untitled.ipynb for stock prediction workflow.
3. Run app.py and auth.py for the application and user management.
4. Check .pkl files for trained model usage.
5. Watch this repository for upcoming AI chatbot integration.

Learning Outcomes

• Data cleaning and preprocessing for ML projects
• Feature engineering for better predictions
• Building, training, and evaluating ML models (supervised learning)
• Deploying models with Python scripts
• Planning and integrating chatbot/AI modules

Keywords

Machine Learning, Stock Price Prediction, Data Science, Internship Ready, Python, Jupyter, Chatbot, ML Model, Regression, Walmart, Project Showcase, SQL, Data Cleaning