In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more.
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深度学习 专项课程deeplearning.ai课程信息
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通过此课程获得实实在在的工作福利
12%
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第 4 门课程（共 5 门）
中级
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
完成时间大约为35 小时
英语（English）
字幕：中文（繁体）, 阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 中文（简体）, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）, 日语
您将获得的技能
Deep LearningFacial Recognition SystemConvolutional Neural NetworkTensorflowObject Detection and Segmentation
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
可灵活调整截止日期
根据您的日程表重置截止日期。
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）
中级
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
完成时间大约为35 小时
英语（English）
字幕：中文（繁体）, 阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 中文（简体）, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）, 日语
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deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
教学大纲 - 您将从这门课程中学到什么
完成时间为 9 小时
Foundations of Convolutional Neural Networks
Implement the foundational layers of CNNs (pooling, convolutions) and stack them properly in a deep network to solve multi-class image classification problems.
完成时间为 9 小时
12 个视频 （总计 140 分钟）, 8 个阅读材料, 3 个测验
完成时间为 9 小时
Deep Convolutional Models: Case Studies
Discover some powerful practical tricks and methods used in deep CNNs, straight from the research papers, then apply transfer learning to your own deep CNN.
完成时间为 9 小时
14 个视频 （总计 127 分钟）, 2 个阅读材料, 3 个测验
完成时间为 9 小时
Object Detection
Apply your new knowledge of CNNs to one of the hottest (and most challenging!) fields in computer vision: object detection.
完成时间为 9 小时
14 个视频 （总计 110 分钟）, 4 个阅读材料, 3 个测验
完成时间为 8 小时
Special Applications: Face recognition & Neural Style Transfer
Explore how CNNs can be applied to multiple fields, including art generation and face recognition, then implement your own algorithm to generate art and recognize faces!
完成时间为 8 小时
11 个视频 （总计 75 分钟）, 6 个阅读材料, 3 个测验
审阅
来自CONVOLUTIONAL NEURAL NETWORKS的热门评论
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.
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 SH 提供Aug 5, 2019
Great content in lectures! Automatic graders for programming assignments can be tricky, and set to old versions of tf sometimes, but answers to these issues are readily found in the discussion forums.
关于 深度学习 专项课程
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.
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