/Image-Classification-Using_Logistic_Regression_Model

Primary LanguageJupyter Notebook

Image Recognition using Logistic Regression 📊

Welcome to my Image Recognition project repository! This project focuses on using Logistic Regression to achieve 96% accuracy in recognizing images based on pixel data.

Project Overview:

  • Objective: Implement Logistic Regression for image classification.
  • Accuracy: Achieved impressive 96% accuracy on test data.
  • Libraries Used: Python NumPy Pandas Matplotlib Seaborn Scikit-learn

Key Features:

  • Data Preprocessing: Utilized Pandas and NumPy for data manipulation and preprocessing.
  • Model Development: Implemented Logistic Regression using Scikit-learn.
  • Evaluation: Evaluated model performance and achieved high accuracy through thorough testing.

Future Work:

  • Experiment with deep learning models for potentially higher accuracy.
  • Refine preprocessing techniques and explore additional feature engineering.

Connect with Me:

Let's connect on LinkedIn to discuss this project and explore more about image recognition and machine learning!