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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

35,320개의 평가
3,706개의 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


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.


Mar 08, 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!

필터링 기준:

Structuring Machine Learning Projects의 3,667개 리뷰 중 2976~3000

교육 기관: Rahul K

Jul 19, 2018

The course is the best available on the online education platforms so far. An excellent instructor and really engaging assignments. You get it all but it lacks availability or reading materials.

교육 기관: mitch d

May 06, 2018

There are some answers on the "flight simulator" that are ambiguously worded, and one that seems to flat-out contradict what Prof. Ng said in lecture. Search the discussion forums for "foggy".

교육 기관: Eric v d K

Dec 28, 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!


교육 기관: Wauters S

Aug 29, 2017

Basic but super relevant and well structure! Things we may all know, but forget to think about... I highly recommand. The only reason why I did not give 5 stars is that it's sometime repetitive

교육 기관: Nicolas B

Jul 28, 2019

Course was really interresting with lot of insights. I would have maybe put even more examples/cases and added more quizz to get more practical training if we apply the pilot training analogy.

교육 기관: Sandeep J

Jan 30, 2018

Great class. Homeworks don't encourage independent thought. It would be nice if the material would spell out the problems that need to be solved more clearly, before describing the solution.

교육 기관: liubai01

Sep 15, 2017

That is a good course that teaches you many useful tricks in machine learning. However, some mistakes in quiz make me feel puzzled. In general, it is a good course that you should not miss.

교육 기관: Rufo S

Sep 19, 2017

Very good course with important topics. The Quiz 2 should be reviewed because has some inconsistencyies has mentioned in the forums. Some more pratical assignment would be also appreciated.

교육 기관: Michael B

Mar 12, 2018

I was a little disappointed that this course didn't have any programming exercises. That being said, I really like how the quizzes make you think of a real world application. Great stuff!

교육 기관: Vassilios V

Feb 11, 2018

Very good advice that is hard to find anywhere else. The quizes however have some ambiguous cases which are borderline wrong. At least they should be explained better after the completion

교육 기관: Radu I

Oct 23, 2017

Interesting opinions on what strategy to take to drive ML projects forward. Here and there you must weigh in with some "numbers" that suit you/your team but it's informative, nonetheless.

교육 기관: Bryan H

May 29, 2018

The course appears to be in development and could be strengthened with programming assignments that take you through an actual mock project. Otherwise, the current content is enjoyable.

교육 기관: Tri W G

Mar 10, 2018

Not so much different with the materials in the Machine Learning course from Prof. Andrew Ng itself. If you don't have the time to finish the ML course, then you should take this one.

교육 기관: Akhil

Jun 28, 2018

A good approach to ML strategy. However, having a programming assignment to better explore results from tweaking models based on the strategies discussed in the course would be great.

교육 기관: Richard J B

Nov 20, 2017

Developing intuition on how to structure projects in deep learning is essential to becoming effective and productive. This course is a good start for gaining that experience quickly.

교육 기관: Iver B

Oct 22, 2018

Valuable information that is well-organized and clearly delivered. Would benefit from a larger number of shorter exercises each week to cement learning after each group of lectures.

교육 기관: vivek v

Jun 23, 2019

This course provided an empirical approach in tackling hurdles in solving most common issues faced by data scientist in solving Machine learning problem in a very simplified manner.

교육 기관: Søren B

Jan 29, 2018

Based on my own experience and comments on the discussion forums, I get the impression that the quizzes have a couple of errors in them that makes it impossible to achieve 100%.

교육 기관: Juan Z

Nov 09, 2019

This course is less pratical and theoretical. I don't mean it is not helpful to me. I think this course might be helpful as guideline when I hand on the real project in future

교육 기관: annestay e

Nov 04, 2019

very good course, but I felt like it was lacking one more week of course to get deeper knowledge about how to really get data sets and how to set them up for real applications.

교육 기관: Christian V

Jul 18, 2019

you may think because the course is shorter will be much easier but the videos has a lot of information to process. I am excited to tried this techniques on real applications!

교육 기관: Ambrose S O O

May 25, 2019

A good course. Provided general high level thinking and reasoning for quick problem solving, data management, multi-tasking, transfer learning, and error reduction techniques.

교육 기관: Sayantan A

May 23, 2018

Not as exciting as the previous courses, but informative nonetheless. A section for handling imbalanced or skewed datasets would be useful, especially for multi-task learning.

교육 기관: Aleksi S

Feb 22, 2018

Not as deep into details as the two first courses in the specialisation, but nevertheless I learnt a lot of techniques that I hope will be feasible when I work on AI projects.

교육 기관: Charles S

Nov 29, 2017

Excellent lectures and notes as always. Great insights and clearly explained. I think we could have used a programming exercise on transfer learning at least in this section.