课程信息

582,702 次近期查看

学生职业成果

13%

通过此课程获得实实在在的工作福利

10%

加薪或升职
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
第 2 门课程(共 4 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
中级

Course 1 of the TensorFlow Specialization, Python coding, and high-school level math are required. ML/DL experience is helpful but not required.

完成时间大约为26 小时
英语(English)
字幕:英语(English), 俄语(Russian), 日语

您将学到的内容有

  • Handle real-world image data

  • Plot loss and accuracy

  • Explore strategies to prevent overfitting, including augmentation and dropout

  • Learn transfer learning and how learned features can be extracted from models

您将获得的技能

Inductive TransferAugmentationDropoutsMachine LearningTensorflow

学生职业成果

13%

通过此课程获得实实在在的工作福利

10%

加薪或升职
可分享的证书
完成后获得证书
100% 在线
立即开始,按照自己的计划学习。
第 2 门课程(共 4 门)
可灵活调整截止日期
根据您的日程表重置截止日期。
中级

Course 1 of the TensorFlow Specialization, Python coding, and high-school level math are required. ML/DL experience is helpful but not required.

完成时间大约为26 小时
英语(English)
字幕:英语(English), 俄语(Russian), 日语

讲师

提供方

deeplearning.ai 徽标

deeplearning.ai

教学大纲 - 您将从这门课程中学到什么

内容评分Thumbs Up97%(5,496 个评分)Info
1

1

完成时间为 7 小时

Exploring a Larger Dataset

完成时间为 7 小时
8 个视频 (总计 18 分钟), 5 个阅读材料, 3 个测验
8 个视频
A conversation with Andrew Ng1分钟
Training with the cats vs. dogs dataset2分钟
Working through the notebook4分钟
Fixing through cropping49
Visualizing the effect of the convolutions1分钟
Looking at accuracy and loss1分钟
Week 1 Wrap up33
5 个阅读材料
Before you Begin: TensorFlow 2.0 and this Course10分钟
The cats vs dogs dataset10分钟
Looking at the notebook10分钟
What you'll see next10分钟
What have we seen so far?10分钟
1 个练习
Week 1 Quiz30分钟
2

2

完成时间为 7 小时

Augmentation: A technique to avoid overfitting

完成时间为 7 小时
7 个视频 (总计 14 分钟), 6 个阅读材料, 3 个测验
7 个视频
Introducing augmentation2分钟
Coding augmentation with ImageDataGenerator3分钟
Demonstrating overfitting in cats vs. dogs1分钟
Adding augmentation to cats vs. dogs1分钟
Exploring augmentation with horses vs. humans1分钟
Week 2 Wrap up37
6 个阅读材料
Image Augmentation10分钟
Start Coding...10分钟
Looking at the notebook10分钟
The impact of augmentation on Cats vs. Dogs10分钟
Try it for yourself!10分钟
What have we seen so far?10分钟
1 个练习
Week 2 Quiz30分钟
3

3

完成时间为 7 小时

Transfer Learning

完成时间为 7 小时
7 个视频 (总计 14 分钟), 5 个阅读材料, 3 个测验
7 个视频
Understanding transfer learning: the concepts2分钟
Coding transfer learning from the inception mode1分钟
Coding your own model with transferred features2分钟
Exploring dropouts1分钟
Exploring Transfer Learning with Inception1分钟
Week 3 Wrap up36
5 个阅读材料
Start coding!10分钟
Adding your DNN10分钟
Using dropouts!10分钟
Applying Transfer Learning to Cats v Dogs10分钟
What have we seen so far?10分钟
1 个练习
Week 3 Quiz30分钟
4

4

完成时间为 7 小时

Multiclass Classifications

完成时间为 7 小时
6 个视频 (总计 12 分钟), 5 个阅读材料, 3 个测验
6 个视频
Moving from binary to multi-class classification44
Explore multi-class with Rock Paper Scissors dataset2分钟
Train a classifier with Rock Paper Scissors1分钟
Test the Rock Paper Scissors classifier2分钟
A conversation with Andrew Ng1分钟
5 个阅读材料
Introducing the Rock-Paper-Scissors dataset10分钟
Check out the code!10分钟
Try testing the classifier10分钟
What have we seen so far?10分钟
Wrap up10分钟
1 个练习
Week 4 Quiz30分钟

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关于 TensorFlow in Practice 专项课程

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework. In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry! AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. Looking for more advanced TensorFlow content? Check out the new TensorFlow: Data and Deployment Specialization....
TensorFlow in Practice

常见问题

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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