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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

4.8
34,872개의 평가
3,640개의 리뷰

강좌 소개

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. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

최상위 리뷰

AM

Nov 23, 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.

WG

Mar 19, 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.

필터링 기준:

Structuring Machine Learning Projects의 3,600개 리뷰 중 226~250

교육 기관: Benji T

Feb 18, 2018

Short course but i think this is the most important course out of the 3 as it is more applied. Everything in this course is new to me... , had to read the discussion for help on the quiz. Hope to appreciate what i learn after i start my deep learning project!

교육 기관: Vijay A

Dec 23, 2017

Knowing the algorithms alone doesn't help much in developing ML applications. We should be able to tackle any problem and drive our project towards the intended goal.This course provides some handy tips and tactics for the same.Well taught as usual. Cheers!!!

교육 기관: YongyiWang

Sep 07, 2017

This course is very useful. The 'Simulator' is very cool. After finishing the homework, I have a better understanding on how do deal with a real project. I'm trying to solve a problem in my work, I think this skills mentioned in the course will help me a lot.

교육 기관: Alexandre D

Aug 28, 2019

It's really nice to have Andrew share his practical knowledge and experience. Paying careful attention to data distributions and doing ErrorAnalysis to learn where to focus your efforts are valuable insights. Thanks for making us all better DL practitioners.

교육 기관: Jonathan L

Dec 18, 2018

This course gives you a good understanding of how to approach deep learning projects and machine learning problems in general. After this course you should feel more comfortable understanding how to structure your projects and better optimize your time use.

교육 기관: Leonard N B

Aug 25, 2017

Andrew provided lots of information in a two-week period due to this the course feels more dense than the previous two. The quiz has also been more challenging. Overall though, it is still top notch teaching from the best. Looking forward to Course 4 and 5.

교육 기관: Debojyoti D

Mar 18, 2019

Prof.Nag and Team, had really gave immense effort to make things brain friendly. Really appreciate the effort to make this so easy going, but conceptually very high content. Recommend not to finish over night, but trick is to go slow and grasp the content.

교육 기관: Ehsan M K

Aug 23, 2017

This course is very important as it offers solutions that don't exist in literature to tackle real DL problems. Andrew Ng is basically teaching you from his vast experience. I highly recommend it esp. for those who want to design / implement DL products.

교육 기관: Eiichi N

Feb 24, 2019

I think this course covers the cases where I tend to bog down and waste time, and has provided me with useful and practical guidelines to get out of them. You should not underestimate the value of this course,

just because there is no coding assignment.

교육 기관: Christopher W

Sep 03, 2019

This course is very good at establishing the fundamentals of 'problem analysis' - something which a lot of analysts actually struggle with. I enjoyed it and found the examples helpful to think through the various steps and types of ML applications.

교육 기관: Ved P G

Apr 15, 2019

Learned a lot about dealing with datasets where training data and test data might not have the same distribution. In a practical deep learning project, a lot of decisions are strategic and this course will definitely help in making better decisions.

교육 기관: Marcin G

Oct 15, 2017

Another great course from Andrew Ng. You will learn how to manage deep learning project and get to know some clever ideas of approaching the project from managerial perspective. You will also get to know important people in deep learning community.

교육 기관: Jonathan S

Aug 18, 2018

I do not think you will find this expert advice elsewhere. And the extended scenarios which the quizzes test give the feeling that I now have real experience (although I do not) making high level decisions about guiding a machine learning project.

교육 기관: Michael D

Mar 05, 2018

An excellent overview of a rarely discussed subject. Often lost amidst the seemingly daily discoveries of new deep learning tricks is need to apply deep learning in real applications. This course did a great job of addressing the latter concern.

교육 기관: Hari K M

Jan 19, 2018

One of the key courses in the specialization besides being short and tricky. The content of this course is exactly that which differentiates between a mere programmer from a data scientist or a machine learning engineer. Do not skip this course.

교육 기관: Vladimir A

Oct 09, 2017

At the very beginning the course seemed to be about self-evident, even trivial things. Now I can't imagine it to be dropped out of the specialization.

Thank you prof. Andrew Ng, you gave us a roadmap to move and saved from many blunders on the way.

교육 기관: Vishal V

Oct 11, 2018

A very insightful course detailing the problems encountered in a real-life deep learning pipeline. The solutions were very intuitively explained and the case study approach reinforced the concepts. The heroes interviews too were very interesting.

교육 기관: Serhii K

Sep 21, 2017

This course give a lot of insights about approaching a machine learning problem. It doesn't contain a lot of concepts or algorithms regarding ML itself, but the course will be very helpful for anyone interested in working on real life ML systems.

교육 기관: Florian B

Sep 25, 2019

Very helpful to get an understanding of how to structure a machine learning project. Furthermore it is a great guide to get a first intuition on where to spend time or fix errors in a machine learning project and where to go on fast. Great work!

교육 기관: Laure G

Aug 09, 2018

Ce cours donne des clés sur comment améliorer son réseau de neurones et en particulier éviter de perdre son temps à chercher dans la mauvaise direction.

Je n'ai pas encore mis en oeuvre cela, mais je pense que cela sera très utile le temps venu.

교육 기관: Luam C T

Nov 02, 2017

It's an amazing course for people without ML experience overall. But if you have some experience (deep learning or not), you'll find a lot of basic tricks that you probably already used or figured out intuitively as you worked on some projects.

교육 기관: Doipayan R

Nov 01, 2019

One of the most helpful 8 to 10 hours of instruction I have ever received in my life. Thanks a lot Andrew, and the entire team for putting this together. I will recommend this course to all my friends and colleagues working in the AI/ML space.

교육 기관: Sayar B

Jul 30, 2018

Perhaps the most important course out of the 5 courses, Professor Ng explains really important concepts often overlooked by a lot of machine learning/ deep learning tutorials. This course will really make your good algorithms great.

Cheers! :)

교육 기관: Gabriel S

Jul 11, 2018

the question on synthetic fog, I would love to know if someone answered to this one right from the first time. It is a designed trap to see if we are just listening to the class and applying or if we really think and work hard on each question

교육 기관: Mahmoud H S

Jul 25, 2019

this is the greatest course I have ever seen in machine learning and deep learning. it gives students the best practice for applying machine learning in real projects and gain a lot of experience from one of the best machine learning experts.