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
課程信息
262,420 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
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）
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初級
完成時間大約為7 小時
建議：2 weeks of study, 3-4 hours/week
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
deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders.
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
4.8
來自STRUCTURING MACHINE LEARNING PROJECTS的熱門評論
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.
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.\n\nBest & thanks again for an awesome course!\n\nEric
由 WG 提供Mar 18, 2019
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.
由 DC 提供Mar 7, 2018
Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!
由 TR 提供Sep 21, 2018
This is a must course in the entire specialization. It covers the step by step procedure to approach and solve a problem. The case studies provided are real world problems which are so much helpful.
由 AP 提供Jun 20, 2019
Really a good course with mostly the theoretical knowledge on some aspects to reuse your model as well as some error analysis. Thoroughly taught with lots of real-life examples, thanks to Andrew Ng.
由 ZZ 提供Apr 6, 2018
A lot of concrete examples, including those in the lectures and in the tests. Gained some thoughts on how to manage a ML project. Thanks Andrew and deeplearning.ai for providing such a great course.
由 NI 提供Nov 10, 2017
Awesome course as always. The course teaches real world practical aspects of how to get started and navigate in the real world projects. The guidelines are actual learnings from years of experience.
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.
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