This project explores the application of image classification and clustering techniques using R. The dataset includes various images categorized by their attributes. We employ Artificial Neural Networks (ANN) to classify images based on their features and assess model performance through accuracy metrics.

clustering analysis

test

The ability to classify and cluster images of various entities is a crucial aspect of modern computer vision and machine learning. This project aims to develop a robust analytical framework for categorizing and grouping images of animals, plants, and fruits. Through systematic data collection, model building, and evaluation, we will explore the performance of different machine learning techniques, including logistic regression and neural networks, to provide insights into the effectiveness of these methods for image classification tasks.