返回到 Transfer Learning for Food Classification
學生對 Coursera Project Network 提供的 Transfer Learning for Food Classification 的評價和反饋
63 個評分
課程概述
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.
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1 - Transfer Learning for Food Classification 的 8 個評論（共 8 個）
創建者 Feng J
•2020年10月8日
I learn a lot of transfer learning by this project. Thank you very much for preparing it so well !
創建者 Deena A
•2021年9月4日
Well organized, enough content and knowledgeable instructor.
創建者 SANJEEV P V
•2020年7月29日
Good course and it is very usefull
創建者 Sarah K
•2020年9月27日
Thanks for the amazing course
創建者 Rayees A L
•2020年8月10日
Great fully satisfied
創建者 Selina S
•2020年10月15日
Good Skills
創建者 VINAYAK M
•2020年7月20日
Excellent
創建者 María N
•2020年9月10日
The instructor does the classes very simple and well informative. The only one issues is the Rhyme app online which does not allow you to reset all the workspace to default mode so I made serious mistakes that lead me to many errors.
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