In this hands-on project, we will train a deep learning model to predict the type of food and then fine tune the model to improve its performance. This project could be practically applied in food industry to detect the type and quality of food. In this 2-hours long project-based course, you will be able to:
- Understand the theory and intuition behind Convolutional Neural Networks (CNNs).
- Understand the theory and intuition behind transfer learning.
- Import Key libraries, dataset and visualize images.
- Perform data augmentation.
- Build a Deep Learning Model using Pre-Trained InceptionResnetV2.
- Compile and fit Deep Learning model to training data.
- Assess the performance of trained CNN and ensure its generalization using various KPIs.