You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how.
提供方
深度学习 专项课程deeplearning.ai课程信息
612,309 次近期查看
学生职业成果
36%
完成这些课程后已开始新的职业生涯
38%
通过此课程获得实实在在的工作福利
14%
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 3 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。
初级
完成时间大约为5 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）
您将获得的技能
Machine LearningDeep LearningInductive TransferMulti-Task Learning
学生职业成果
36%
完成这些课程后已开始新的职业生涯
38%
通过此课程获得实实在在的工作福利
14%
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 3 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。
初级
完成时间大约为5 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）
提供方
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 2 小时
ML Strategy (1)
完成时间为 2 小时
13 个视频 （总计 100 分钟）, 1 个阅读材料, 1 个测验
13 个视频
Orthogonalization10分钟
Single number evaluation metric7分钟
Satisficing and Optimizing metric5分钟
Train/dev/test distributions6分钟
Size of the dev and test sets5分钟
When to change dev/test sets and metrics11分钟
Why human-level performance?5分钟
Avoidable bias6分钟
Understanding human-level performance11分钟
Surpassing human-level performance6分钟
Improving your model performance4分钟
Andrej Karpathy interview15分钟
1 个阅读材料
Machine Learning flight simulator2分钟
1 个练习
Bird recognition in the city of Peacetopia (case study)45分钟
完成时间为 3 小时
ML Strategy (2)
完成时间为 3 小时
11 个视频 （总计 132 分钟）
11 个视频
Cleaning up incorrectly labeled data13分钟
Build your first system quickly, then iterate6分钟
Training and testing on different distributions10分钟
Bias and Variance with mismatched data distributions18分钟
Addressing data mismatch10分钟
Transfer learning11分钟
Multi-task learning12分钟
What is end-to-end deep learning?11分钟
Whether to use end-to-end deep learning10分钟
Ruslan Salakhutdinov interview17分钟
1 个练习
Autonomous driving (case study)45分钟
审阅
来自STRUCTURING MACHINE LEARNING PROJECTS的热门评论
由 MG 提供Mar 30, 2020
It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.
由 JB 提供Jul 1, 2020
While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).
由 EK 提供Dec 27, 2017
Loved the course, and the simulation was great. Doing an actual transfer learning programming exercise in TensorFlow could be an awesome addition. Best & thanks again for an awesome course!\n\nEric
由 AM 提供Nov 22, 2017
I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
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.
常见问题
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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