Chevron Left
返回到 Classification with Transfer Learning in Keras

学生对 Coursera Project Network 提供的 Classification with Transfer Learning in Keras 的评价和反馈

4.5
154 个评分

课程概述

In this 1.5 hour long project-based course, you will learn to create and train a Convolutional Neural Network (CNN) with an existing CNN model architecture, and its pre-trained weights. We will use the MobileNet model architecture along with its weights trained on the popular ImageNet dataset. By using a model with pre-trained weights, and then training just the last layers on a new dataset, we can drastically reduce the training time required to fit the model to the new data . The pre-trained model has already learned to recognize thousands on simple and complex image features, and we are using its output as the input to the last layers that we are training. In order to be successful in this project, you should be familiar with Python, Neural Networks, and CNNs. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

热门审阅

AS

Jun 20, 2020

How else would I have learned this? What a great fast way to apply a concept in real code.

SK

May 28, 2020

Everything was as per description! Need more advanced tasks. Thanks, Amit Sir!

筛选依据:

1 - Classification with Transfer Learning in Keras 的 19 个评论(共 19 个)

创建者 Mudit D

Jul 1, 2020

创建者 Harshad L

Jun 7, 2020

创建者 Alex S

Jun 20, 2020

创建者 Sarah K

May 29, 2020

创建者 M V

Jun 3, 2020

创建者 EDWIN J

Jun 15, 2020

创建者 Kamlesh C

Jun 20, 2020

创建者 Gaikwad N

Jul 23, 2020

创建者 p s

Jun 25, 2020

创建者 tale p

Jun 23, 2020

创建者 Patil B

May 2, 2020

创建者 Ali E

Mar 22, 2020

创建者 Yubesny V

Nov 13, 2020

创建者 Utkarsh R

Mar 24, 2020

创建者 Thanda H

Sep 11, 2020

创建者 Mr. M K S E

May 8, 2020

创建者 Raj v

Jul 14, 2020

创建者 Rathi.R

Jun 11, 2020

创建者 Jorge G

Feb 25, 2021