How to Classify Flowers Using Deep Learning

Learn to classify flowers using deep learning in this 37-minute tutorial. Build an image classification model with a convolutional neural network using TensorFlow and Keras on a flowers dataset. Follow along as the instructor guides you through installation, dataset preparation, model creation, training, and testing. Explore practical applications by predicting flower types for individual images and image lists. Access code and instructions on GitHub, with a note on a fixed bug. Gain insights into recommended hardware for TensorFlow model training and useful cameras for computer vision projects. Enhance your skills in Python, CNN, and deep learning with suggested resources and books.

Intro
Installation - Python libraries
Download the dataset and prepare the folders
create the CNN model using Python
Test the model - Predict one flower image
Test the model on list of flower images