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第 4 門課程(共 5 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為21 小時

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

英語(English)

字幕:中文(繁體), 中文(簡體), 韓語, 土耳其語(Turkish), 英語(English), 西班牙語(Spanish), 日語...

您將獲得的技能

Facial Recognition SystemTensorflowConvolutional Neural NetworkArtificial Neural Network
學習Course的學生是
  • Data Scientists
  • Machine Learning Engineers
  • Biostatisticians
  • Scientists
  • Researchers

第 4 門課程(共 5 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為21 小時

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

英語(English)

字幕:中文(繁體), 中文(簡體), 韓語, 土耳其語(Turkish), 英語(English), 西班牙語(Spanish), 日語...

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 6 小時

Foundations of Convolutional Neural Networks

12 個視頻 (總計 140 分鐘), 4 個閱讀材料, 3 個測驗
12 個視頻
Edge Detection Example11分鐘
More Edge Detection7分鐘
Padding9分鐘
Strided Convolutions9分鐘
Convolutions Over Volume10分鐘
One Layer of a Convolutional Network16分鐘
Simple Convolutional Network Example8分鐘
Pooling Layers10分鐘
CNN Example12分鐘
Why Convolutions?9分鐘
Yann LeCun Interview27分鐘
4 個閱讀材料
Strided convolutions *CORRECTION*1分鐘
Simple Convolutional Network Example *CORRECTION*1分鐘
CNN Example *CORRECTION*1分鐘
Why Convolutions? *CORRECTION*1分鐘
1 個練習
The basics of ConvNets20分鐘
2
完成時間為 5 小時

Deep convolutional models: case studies

11 個視頻 (總計 99 分鐘), 1 個閱讀材料, 2 個測驗
11 個視頻
Classic Networks18分鐘
ResNets7分鐘
Why ResNets Work9分鐘
Networks in Networks and 1x1 Convolutions6分鐘
Inception Network Motivation10分鐘
Inception Network8分鐘
Using Open-Source Implementation4分鐘
Transfer Learning8分鐘
Data Augmentation9分鐘
State of Computer Vision12分鐘
1 個閱讀材料
Inception Network Motivation *CORRECTION*1分鐘
1 個練習
Deep convolutional models20分鐘
3
完成時間為 4 小時

Object detection

10 個視頻 (總計 85 分鐘), 2 個閱讀材料, 2 個測驗
10 個視頻
Landmark Detection5分鐘
Object Detection5分鐘
Convolutional Implementation of Sliding Windows11分鐘
Bounding Box Predictions14分鐘
Intersection Over Union4分鐘
Non-max Suppression8分鐘
Anchor Boxes9分鐘
YOLO Algorithm7分鐘
(Optional) Region Proposals6分鐘
2 個閱讀材料
Convolutional Implementation of Sliding Windows *CORRECTION*1分鐘
YOLO algorithm *CORRECTION*1分鐘
1 個練習
Detection algorithms20分鐘
4
完成時間為 5 小時

Special applications: Face recognition & Neural style transfer

11 個視頻 (總計 76 分鐘), 3 個閱讀材料, 3 個測驗
11 個視頻
One Shot Learning4分鐘
Siamese Network4分鐘
Triplet Loss15分鐘
Face Verification and Binary Classification6分鐘
What is neural style transfer?2分鐘
What are deep ConvNets learning?7分鐘
Cost Function3分鐘
Content Cost Function3分鐘
Style Cost Function13分鐘
1D and 3D Generalizations9分鐘
3 個閱讀材料
Triplet Loss *CORRECTION*1分鐘
Face Verification and Binary Classification *CORRECTION*1分鐘
Style Cost *CORRECTION*1分鐘
1 個練習
Special applications: Face recognition & Neural style transfer20分鐘
4.9
3007 個審閱Chevron Right

37%

完成這些課程後已開始新的職業生涯

37%

通過此課程獲得實實在在的工作福利

11%

加薪或升職

來自Convolutional Neural Networks的熱門評論

創建者 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.

創建者 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.

講師

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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

關於 deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

關於 深度学习 專項課程

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....
深度学习

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