课程信息
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第 4 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为21 小时

建议:4 weeks of study, 4-5 hours/week...

英语(English)

字幕:中文(繁体), 中文(简体), 韩语, 土耳其语(Turkish), 英语(English), 西班牙语(Spanish), 日语...

您将获得的技能

Facial Recognition SystemTensorflowConvolutional Neural NetworkArtificial Neural Network
学习Course的学生是
  • Data Scientists
  • Machine Learning Engineers
  • Biostatisticians
  • Researchers
  • Research Assistants

第 4 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为21 小时

建议:4 weeks of study, 4-5 hours/week...

英语(English)

字幕:中文(繁体), 中文(简体), 韩语, 土耳其语(Turkish), 英语(English), 西班牙语(Spanish), 日语...

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 6 小时

Foundations of Convolutional Neural Networks

12 个视频 (总计 140 分钟), 4 个阅读材料, 3 个测验
12 个视频
Edge Detection Example11分钟
More Edge Detection7分钟
Padding9分钟
Strided Convolutions9分钟
Convolutions Over Volume10分钟
One Layer of a Convolutional Network16分钟
Simple Convolutional Network Example8分钟
Pooling Layers10分钟
CNN Example12分钟
Why Convolutions?9分钟
Yann LeCun Interview27分钟
4 个阅读材料
Strided convolutions *CORRECTION*1分钟
Simple Convolutional Network Example *CORRECTION*1分钟
CNN Example *CORRECTION*1分钟
Why Convolutions? *CORRECTION*1分钟
1 个练习
The basics of ConvNets20分钟
2
完成时间为 5 小时

Deep convolutional models: case studies

11 个视频 (总计 99 分钟), 1 个阅读材料, 2 个测验
11 个视频
Classic Networks18分钟
ResNets7分钟
Why ResNets Work9分钟
Networks in Networks and 1x1 Convolutions6分钟
Inception Network Motivation10分钟
Inception Network8分钟
Using Open-Source Implementation4分钟
Transfer Learning8分钟
Data Augmentation9分钟
State of Computer Vision12分钟
1 个阅读材料
Inception Network Motivation *CORRECTION*1分钟
1 个练习
Deep convolutional models20分钟
3
完成时间为 4 小时

Object detection

10 个视频 (总计 85 分钟), 2 个阅读材料, 2 个测验
10 个视频
Landmark Detection5分钟
Object Detection5分钟
Convolutional Implementation of Sliding Windows11分钟
Bounding Box Predictions14分钟
Intersection Over Union4分钟
Non-max Suppression8分钟
Anchor Boxes9分钟
YOLO Algorithm7分钟
(Optional) Region Proposals6分钟
2 个阅读材料
Convolutional Implementation of Sliding Windows *CORRECTION*1分钟
YOLO algorithm *CORRECTION*1分钟
1 个练习
Detection algorithms20分钟
4
完成时间为 5 小时

Special applications: Face recognition & Neural style transfer

11 个视频 (总计 76 分钟), 3 个阅读材料, 3 个测验
11 个视频
One Shot Learning4分钟
Siamese Network4分钟
Triplet Loss15分钟
Face Verification and Binary Classification6分钟
What is neural style transfer?2分钟
What are deep ConvNets learning?7分钟
Cost Function3分钟
Content Cost Function3分钟
Style Cost Function13分钟
1D and 3D Generalizations9分钟
3 个阅读材料
Triplet Loss *CORRECTION*1分钟
Face Verification and Binary Classification *CORRECTION*1分钟
Style Cost *CORRECTION*1分钟
1 个练习
Special applications: Face recognition & Neural style transfer20分钟
4.9
3165 个审阅Chevron Right

37%

完成这些课程后已开始新的职业生涯

37%

通过此课程获得实实在在的工作福利

12%

加薪或升职

来自Convolutional Neural Networks的热门评论

创建者 RKSep 2nd 2019

This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.

创建者 AGJan 13th 2019

Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.

讲师

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Andrew Ng

CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain
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Head Teaching Assistant - Kian Katanforoosh

Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
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Teaching Assistant - Younes Bensouda Mourri

Mathematical & Computational Sciences, Stanford University, deeplearning.ai
Computer Science

关于 deeplearning.ai

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关于 深度学习 专项课程

If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI....
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