Deep Learning - Convolutional Neural Networks with TensorFlow - Transfer Learning Code (Part 2)

The video tutorial covers transfer learning without data augmentation using a collab notebook. It begins with setting up the environment and preparing data, followed by configuring a pre-trained model. The tutorial then explains feature extraction from images and transforming data into a tabular format. Finally, it demonstrates model training and evaluation, comparing results with and without data augmentation, highlighting the efficiency and accuracy of the approach.

How does the performance of the model change when using scaling versus not using scaling?

What were the results of using logistic regression included in Scikit-Learn compared to the script with data augmentation?

What observations were made regarding the speed of training with and without data augmentation?