CIFAR-10 Transfer Learning with VGG16

This project demonstrates image classification on the CIFAR-10 dataset using transfer learning with the pre-trained VGG16 model. The implementation is done in Google Colab and includes data preprocessing, model adaptation, training, evaluation, and result visualization using TensorFlow and Keras.

Installation

To run this project in Google Colab, you don't need to install anything locally. All necessary packages are available in the Colab environment.

Project Details

The project consists of the following steps:

1. Setup and Data Preparation: Load and preprocess the CIFAR-10 dataset.
2. Load and Adapt Pre-trained Model: Use the VGG16 model pre-trained on ImageNet and adapt it for CIFAR-10 classification.
3. Train the Model: Train the adapted model using the training data.
4. Evaluate the Model: Evaluate the model's performance on the test data.
5. Visualize Results: Plot training and validation accuracy and loss.