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.

Applying the K-Means algorithm on the Pokemon dataset

Here I have developed an Artificial Neural Network (ANN) model to predict the survival of patients who underwent surgery for breast cancer based on the Haberman’s Survival Data.