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Avis et commentaires pour l'étudiant pour Structuring Machine Learning Projects par deeplearning.ai

4.8
27,874 notes
2,966 avis

À propos du cours

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....

Meilleurs avis

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.

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1 - 25 sur 2,970 Examens pour Structuring Machine Learning Projects

par Liu H

Jun 11, 2019

This course would be immensely helpful for those who have not started on their first machine learning project. However, the insights shared are quite commonsensical and intuitive for those who have already had some minimal experience in machine learning. This course also does not feel as substantial as the other courses in the specialization, though the tips provided are definitely valuable.

par ABHISHEK K

May 31, 2019

I recommend this course. This will be a bit of theoretical which is good. It will talk about real world scenarios over the errors which is what we deal in day-to-day life and how to deal with it.

par Nazarii N

May 25, 2019

more practice!

par Walter G

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.

par Matei I

Feb 16, 2019

I'm glad I spent some time on the "Flight simulator" assignments in this course. It's the first time in the specialization when I actually found the quiz questions challenging, and that's a welcome change. However, I didn't learn too much from the lectures. They were too repetitive, either repeating themselves or the material from the previous course. One or two videos could also do with better editing work: I could hear Andrew making a soundcheck, and there's a 30sec segment that's played twice in a row. Overall, it's probably worth doing this course, given that it requires very little time, and the assignments are useful.

par ANKIT M

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.

par Moaz M T

Jun 26, 2019

Just fantastic!

par Beibit

Jun 26, 2019

somewhat general

par SeungHoon L

Jun 26, 2019

Exceptionally constructive lecture for Machine Learning practitioners!!

par Lester A S D C

Jun 25, 2019

Useful knowledge regarding the efficient practices in the application of machine learning. Mentors doesn't seem as responsive though, compared to the other courses of the specialization. Quizzes were helpful, but needs more justification for some of the correct answers.

par Pak S H

Jun 25, 2019

Very brief yet insightful course!

par Ivan L

Jun 25, 2019

Most of the material was quite useful, but some was, perhaps, too obvious. Also, some things were discussed too thoroughly, and, in my opinion, that was a waste of time.

par Pedro R

Jun 25, 2019

Very good content quality and challenging quizzes.

par Wang Z

Jun 25, 2019

Intuitive course. Helpful.

par Victor R

Jun 24, 2019

Fantastic course! Learned a lot! Do it in combination with extra resources for maximum effect

par Dimitry I

Jun 24, 2019

Another good course in the Deep Learning specialization. Thank you to Prof Ng and the rest of the team.

par Nilesh M

Jun 24, 2019

Very good course and covered lot of interesting and practical cases

par 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.

par Gourav S

Jun 22, 2019

nothing less than brilliant

par Martin W

Jun 22, 2019

Awesome!

par Anshu S P

Jun 21, 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.

par etangyushan

Jun 21, 2019

good good good

par William G

Jun 21, 2019

Really interesting !

par Erie F B

Jun 20, 2019

excellent

par Yafremau N

Jun 20, 2019

Great way to understand step by step all important aspects of creating a machine learning project. Finding out what problems can be faced while creating a model and ways to fix them.