This project aims to develop an AI application capable of recognizing different species of flowers using deep learning techniques. The application can be integrated into various platforms, such as mobile apps, to provide users with information about the flowers they encounter. By leveraging a pre-trained image classifier trained on a dataset containing 102 flower categories, the application can accurately identify different types of flowers from images captured by the user's device.

Load and Preprocess the Image Dataset: The project begins with loading and preprocessing the image dataset, which consists of labeled images of various flower species. Train the Image Classifier: Next, the image classifier is trained on the preprocessed dataset using deep learning techniques. This involves constructing and training a neural network model to recognize different flower species based on their visual features. Use the Trained Classifier to Predict Image Content: Once the classifier is trained, it can be used to predict the content of new images, allowing users to identify flower species in real-time.