Transfer Learning for Food Classification

4.6

64 個評分

提供方

3,959 人已註冊

在此指導項目中,您將:
2 hours
初級
無需下載
分屏視頻
英語(English)
僅限桌面

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.

您要培養的技能

  • Deep Learning

  • Machine Learning

  • Python Programming

  • Artificial Intelligence(AI)

  • Computer Vision

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

審閱

來自TRANSFER LEARNING FOR FOOD CLASSIFICATION的熱門評論

查看所有評論

常見問題