This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images.
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深度学习 专项课程deeplearning.ai课程信息
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12%
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完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 5 门）
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中级
完成时间大约为20 小时
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
学生职业成果
36%
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
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 4 门课程（共 5 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
完成时间大约为20 小时
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
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deeplearning.ai
Founded by Andrew Ng, deeplearning.ai is on a mission to make world-class AI education accessible to people around the globe so that we can all benefit from an AI-powered future.
教学大纲 - 您将从这门课程中学到什么
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.
完成时间为 6 小时
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 ConvNets30分钟
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.
完成时间为 5 小时
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 models30分钟
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.
完成时间为 4 小时
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 algorithms30分钟
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!
完成时间为 5 小时
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 transfer30分钟
审阅
来自CONVOLUTIONAL NEURAL NETWORKS的热门评论
由 RK 提供Sep 1, 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.
由 AR 提供Jul 11, 2020
I really enjoyed this course, it would be awesome to see al least one training example using GPU (maybe in Google Colab since not everyone owns one) so we could train the deepest networks from scratch
由 RS 提供Dec 11, 2019
Great Course Overall One thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.
由 AG 提供Jan 12, 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.
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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退款政策是如何规定的？
如果订阅，您可以获得 7 天免费试听，在此期间，您可以取消课程，无需支付任何罚金。在此之后，我们不会退款，但您可以随时取消订阅。请阅读我们完整的退款政策。
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