Transfer Learning for Food Classification

4.6
stars

64 ratings

Offered By

3,959 already enrolled

In this Guided Project, you will:
2 hours
Beginner
No download needed
Split-screen video
English
Desktop only

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.

Skills you will develop

  • Deep Learning

  • Machine Learning

  • Python Programming

  • Artificial Intelligence(AI)

  • Computer Vision

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Reviews

TOP REVIEWS FROM TRANSFER LEARNING FOR FOOD CLASSIFICATION

View all reviews

Frequently Asked Questions