返回到 Transfer Learning for Food Classification
学生对 Coursera Project Network 提供的 Transfer Learning for Food Classification 的评价和反馈
62 个评分
课程概述
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 个评论（共 8 个）
创建者 Feng J
•Oct 8, 2020
I learn a lot of transfer learning by this project. Thank you very much for preparing it so well !
创建者 Deena A
•Sep 4, 2021
Well organized, enough content and knowledgeable instructor.
创建者 SANJEEV P V
•Jul 29, 2020
Good course and it is very usefull
创建者 Sarah K
•Sep 27, 2020
Thanks for the amazing course
创建者 Rayees A L
•Aug 10, 2020
Great fully satisfied
创建者 Selina S
•Oct 15, 2020
Good Skills
创建者 VINAYAK M
•Jul 20, 2020
Excellent
创建者 María N
•Sep 10, 2020
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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