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.

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Feel free to contribute or raise issues for improvements!