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返回到 Convolutional Neural Networks in TensorFlow

学生对 DeepLearning.AI 提供的 Convolutional Neural Networks in TensorFlow 的评价和反馈

4.7
8,216 个评分

课程概述

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the DeepLearning.AI TensorFlow Developer Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 2 of the DeepLearning.AI TensorFlow Developer Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. You will explore how to work with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

热门审阅

FJ

Apr 28, 2020

This course awesome, but the notebook from coursera "i think" doesn't support any experiment we want, so we have to do it on google colab. But great, limitation is okay as long it's still graded

AK

Jun 4, 2020

Laurence Moroney is the best. Before taking up the course, i didnt know anything about the AI or ML or Tensorflow. The concepts were explained in such a manner that anyone can learn Tensorflow.

筛选依据:

1176 - Convolutional Neural Networks in TensorFlow 的 1200 个评论(共 1,269 个)

创建者 Sajal C

Mar 31, 2020

Course is good however there can be programming assignments for better practice.

创建者 Javier I R

Nov 15, 2020

Great course, but the last exam was miles away from the things presented on it.

创建者 Ashish J

Jul 3, 2020

this could have been better if object detection and segmentation was a part of

创建者 Enyang W

Nov 6, 2019

too easy! not much to learn actually. all the videos could be one lesson only

创建者 vedansh s

Sep 13, 2019

The concepts are not as clear as in other courses.

Dissapointed a little bit

创建者 Wellington B

Aug 4, 2019

need to watch Andrew Ng's course on deep learning before watching this one

创建者 Alan H

Jul 25, 2021

The final exercise its really unclear on instructions and tools to use

创建者 Aditya S

Jan 16, 2021

Week 4 assignment has a faulty csv file. Labels not correctly loaded

创建者 Joey Y

Aug 4, 2019

The course seems to be getting more loose than the first course.

创建者 Moustafa S

Jun 26, 2020

the same problems with the auto graders, it's exhausting sadly

创建者 Pranav H

Dec 1, 2019

Coding exercises should be made compulsory and for the grade

创建者 Eyal B

Feb 16, 2020

Didn't provide a real understanding for transfer learning

创建者 MOUAFEK A

Jan 4, 2020

not much of insights or details, and it's too easy!

创建者 Deleted A

Apr 22, 2021

The lab exercises for week 4 needs to be changed

创建者 Alejo G

Oct 6, 2019

A lot of boilerplate code with few new concepts

创建者 Mikołaj M

Oct 12, 2020

The course covers elementary techniques.

创建者 Victor S

Sep 4, 2020

Useful course. Just a bit unstructured.

创建者 Param O

Jul 30, 2021

The grader keeps running out of memory

创建者 Bojiang J

Mar 7, 2020

Content too easy and not engaging....

创建者 Jorge E

Sep 21, 2021

Se repiten varios temas del curso 1

创建者 Aymen M

Mar 20, 2021

The last assignment is malformed

创建者 Navid H

Sep 15, 2019

I wish it had real assignments

创建者 Samyak J

Aug 2, 2020

exercises are not very clear

创建者 Paula S

Apr 6, 2020

course is a little too easy.

创建者 Pallavi

Mar 12, 2020

It was not great and good