F l o w e r C l a s s i f i c a t i o n

Have you ever wondered how a computer can recognize different types of flowers just by looking at pictures?

In this project, we build and train a Convolutional Neural Network (CNN) to classify flower images into five categories:

Daisy

Sunflower

Rose

Tulip

Dandelion

The dataset is organized in folders by class, and we use TensorFlow and Keras to build, train, and evaluate the model.

The goal is to achieve a reasonable accuracy on the validation set using a simple yet effective CNN architecture.

If you're curious about how a beginner built a model that reached over 70% accuracy on real image data, follow

along and explore this exciting intersection of AI and nature — one flower at a time