课程信息
4.8
15,506 个评分
2,052 个审阅
专项课程

第 4 门课程(共 5 门),位于

100% online

100% online

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为21 小时

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

英语(English)

字幕:英语(English), 中文(繁体), 中文(简体), 韩语, 日语...

您将获得的技能

Facial Recognition SystemTensorflowConvolutional Neural NetworkArtificial Neural Network
专项课程

第 4 门课程(共 5 门),位于

100% online

100% online

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

完成时间(小时)

完成时间大约为21 小时

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

英语(English)

字幕:英语(English), 中文(繁体), 中文(简体), 韩语, 日语...

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 6 小时

Foundations of Convolutional Neural Networks

Learn to implement the foundational layers of CNNs (pooling, convolutions) and to stack them properly in a deep network to solve multi-class image classification problems....
Reading
12 个视频(共 140 分钟), 3 个测验
Video12 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
Quiz1 个练习
The basics of ConvNets20分钟
2
完成时间(小时)
完成时间为 5 小时

Deep convolutional models: case studies

Learn about the practical tricks and methods used in deep CNNs straight from the research papers. ...
Reading
11 个视频(共 99 分钟), 2 个测验
Video11 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
Quiz1 个练习
Deep convolutional models20分钟
3
完成时间(小时)
完成时间为 4 小时

Object detection

Learn how to apply your knowledge of CNNs to one of the toughest but hottest field of computer vision: Object detection....
Reading
10 个视频(共 85 分钟), 2 个测验
Video10 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
Quiz1 个练习
Detection algorithms20分钟
4
完成时间(小时)
完成时间为 5 小时

Special applications: Face recognition & Neural style transfer

Discover how CNNs can be applied to multiple fields, including art generation and face recognition. Implement your own algorithm to generate art and recognize faces!...
Reading
11 个视频(共 76 分钟), 3 个测验
Video11 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
Quiz1 个练习
Special applications: Face recognition & Neural style transfer20分钟
4.8
职业方向

38%

完成这些课程后已开始新的职业生涯
工作福利

83%

通过此课程获得实实在在的工作福利

热门审阅

创建者 EBNov 3rd 2017

Wonderful course. Covers a wide array of immediately appealing subjects: from object detection to face recognition to neural style transfer, intuitively motivate relevant models like YOLO and ResNet.

创建者 DGFeb 14th 2018

Too much hand-holding during assignments, although still very good directions. Obviously the issue with the final programming assignment needs to be addressed. Fantastic lecture material, as always.

讲师

Avatar

Andrew Ng

Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/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

关于 deeplearning.ai

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

关于 Deep Learning 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....
Deep Learning

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