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- Level Beginner
- Duration 3 hours
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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.Auto Summary
Discover "Transfer Learning for Food Classification," a beginner-friendly course in IT & Computer Science on Coursera. Learn to train and fine-tune deep learning models for food prediction in just 180 minutes. Enjoy free access and hands-on experience under expert guidance. Perfect for aspiring data scientists and AI enthusiasts!