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codealpha_tasks

This repository contains a collection of Python projects developed as part of the CodeAlpha tasks. Each project demonstrates the application of machine learning, deep learning, or data analysis techniques on various datasets.

Contents

  • creditCard.py: Credit card-related data analysis and prediction script.
  • data.csv: Dataset used for Credit Card detection.
  • data/: Downloaded data from the internet for Hand written number recognition.
  • diseasePrediction.py: Script for disease prediction using machine learning.
  • hand-written-number-cnn.py: Convolutional Neural Network implementation for handwritten number recognition.
  • handWrittenNumber.py: Handwritten number recognition using scikit library.
  • img_1.jpg, img_2.jpg, img_3.jpg: Sample images used for demonstration of handwritten number recognition.
  • model_state.pt: Saved PyTorch model state for the projects.
  • model_state.pt: Saved PyTorch model state for the handwritten number recognition project.

Getting Started

  1. Clone the repository:

    git clone https://github.com/Arkz-Deepak/codealpha_tasks.git
    cd codealpha_tasks
  2. Install requirements:

    • Most scripts require Python 3.x and common ML/DL libraries such as numpy, pandas, scikit-learn, and PyTorch.
    • You can install dependencies with:
      pip install numpy pandas scikit-learn torch
  3. Run the scripts:

    • Example for running the CNN for handwritten digit recognition:

      python hand-written-number-cnn.py
    • For disease prediction or credit card analysis, run the respective Python files:

      python diseasePrediction.py
      python creditCard.py

Notes

  • The repository includes large files such as data.csv and model_state.pt. Ensure you have sufficient disk space to clone and work with these files.
  • For specific details about each script, please refer to the comments inside each file.

Feel free to contribute or raise issues for improvements!