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 專項課程deeplearning.ai課程信息
634,009 次近期查看
學生職業成果
36%
完成這些課程後已開始新的職業生涯
38%
通過此課程獲得實實在在的工作福利
14%
加薪或升職
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 3 門課程（共 5 門）
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
完成時間大約為5 小時
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）
您將獲得的技能
Machine LearningDeep LearningInductive TransferMulti-Task Learning
學生職業成果
36%
完成這些課程後已開始新的職業生涯
38%
通過此課程獲得實實在在的工作福利
14%
加薪或升職
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
第 3 門課程（共 5 門）
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
完成時間大約為5 小時
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）
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.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 2 小時
ML Strategy (1)
完成時間為 2 小時
13 個視頻 （總計 100 分鐘）, 1 個閱讀材料, 1 個測驗
13 個視頻
Orthogonalization10分鐘
Single number evaluation metric7分鐘
Satisficing and Optimizing metric5分鐘
Train/dev/test distributions6分鐘
Size of the dev and test sets5分鐘
When to change dev/test sets and metrics11分鐘
Why human-level performance?5分鐘
Avoidable bias6分鐘
Understanding human-level performance11分鐘
Surpassing human-level performance6分鐘
Improving your model performance4分鐘
Andrej Karpathy interview15分鐘
1 個閱讀材料
Machine Learning flight simulator2分鐘
1 個練習
Bird recognition in the city of Peacetopia (case study)45分鐘
完成時間為 3 小時
ML Strategy (2)
完成時間為 3 小時
11 個視頻 （總計 132 分鐘）
11 個視頻
Cleaning up incorrectly labeled data13分鐘
Build your first system quickly, then iterate6分鐘
Training and testing on different distributions10分鐘
Bias and Variance with mismatched data distributions18分鐘
Addressing data mismatch10分鐘
Transfer learning11分鐘
Multi-task learning12分鐘
What is end-to-end deep learning?11分鐘
Whether to use end-to-end deep learning10分鐘
Ruslan Salakhutdinov interview17分鐘
1 個練習
Autonomous driving (case study)45分鐘
審閱
來自STRUCTURING MACHINE LEARNING PROJECTS的熱門評論
由 AM 提供2017年11月22日
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.
由 EK 提供2017年12月27日
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 MG 提供2020年3月30日
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 WG 提供2019年3月18日
Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.
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.
常見問題
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:
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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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