Deep Learning Essentials — (4) VGG-16

1. 1Build a VGG-16 model using Keras or TensorFlow
2. 2Run the model on a dataset of images to train and test its performance
3. 3Configure the model's hyperparameters to optimize its accuracy
4. 4Test the model's performance on a validation set
5. 5Apply the trained model to real-world image classification tasks

Data scientists and software engineers on a team can benefit from understanding VGG-16 for building image classification models, and product managers can leverage this knowledge to inform product decisions

💡 VGG-16 is a pre-trained convolutional neural network (CNN) model that can be fine-tuned for specific image classification tasks

📸 Learn VGG-16 for image classification #deeplearning #computerVision