Chevron Left
Voltar para Structuring Machine Learning Projects

Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição deeplearning.ai

4.8
estrelas
36,241 classificações
3,866 avaliações

Sobre o curso

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....

Melhores avaliações

MG

Mar 31, 2020

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.

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.

Filtrar por:

3176 — 3200 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por 钟胜杰

Nov 19, 2018

The courses of this two weeks make me confused because i have't built a machine learning systems fully by myself yet , so i found those classes boring.0.0

por Robert N C

Aug 02, 2018

Not as helpful or practical as earlier lessons, but nonetheless important high-level advice. Perhaps there was a better way to test knowledge than a quiz?

por Simon S

Oct 23, 2018

Still a great course, but compared to the pervious two, this seems to be a bit less useful and practical and there are a few mistakes with cutting, etc.

por BINGNI G

Sep 12, 2018

It may be useful in the future, but since I don't have any large project experience in the real world, I feel a little boring while taking this course.

por Osbert Z

Feb 16, 2018

Some content was a bit superficial. Many concepts regarding approach to machine learning projects were useful. Found the "flight simulators" were not s

por John F

Jan 28, 2018

Quite a lot useful information for structuring deep learning projects, but also quite some errors in the course contents. Hope them will be fixed soon.

por John E

Oct 04, 2017

Overall a nice approach to understand how to tune the learning algorithms. There are some production/editing issues in the videos that are distracting.

por eddy k

Oct 30, 2017

excellent practical and insightful strategies from years of andrew's experience, i wish there were more hands on labs to practice some of the concepts

por Robert P

Apr 17, 2018

The content is well worth going through. While the "flight simulator" approach was certainly beneficial, I wish there had been programming exercises.

por Felipe M

Jan 07, 2018

The course is good, as I would expect of Andrew, however, I feel like the standards of editing the videos has fallen quite a bit since the ML course.

por KISHOR

Mar 30, 2020

this course was a little boring, but it covers all the necessary concepts about the error analysis and strategies to be followed in machine learning

por am

Jan 19, 2018

Good course! Focusing on strategies on how to start well and manage a DL project.

But very vague! Hoped to have more thery & a usecase on the topic

por Frank H

Nov 18, 2017

I had some problems answering some questions correctly since there was no specific emphasis in the lectures and I was somehow unsure how to reply.

por Gokhan A

Sep 18, 2017

It has nice discussions on the practical aspects of Deep Learning projects, but I wish it had more Math, and it had more programming assignments.

por Bradly M

Apr 03, 2019

This course was relatively short, and the quality of the materials (lecture videos, quiz text) was somewhat poorer than in the previous courses.

por Eric S

Aug 30, 2017

Good practical advice. I would have added something about agile development and possibly practical advice on NN architectures (depth and size).

por Sujay K

Mar 25, 2018

The course would have been more interesting if we had some programming assignments. Hands on experience into some of these cases really help.

por Daniel M

Jan 14, 2018

Unique course in the sense that teaches important topics that are rarely seen in the literature and are fundamental in designing AI projects.

por Hagay G

Apr 09, 2019

Had some pretty great info for junior Project Managers, for some reason, it's also hiding some extremely important info about end-to-end DL.

por Mohamed M H M A

Apr 22, 2018

Some of the videos weren't of good quality. Also, I was expecting doing a real project not to make decisions based on different scenarios.

por Nikolai K

Oct 03, 2017

Good course overall, would have liked to have the in-depth programming assignments though, those really made the other courses stand out.

por Shashank S S

Jul 08, 2019

Learned various ways to structure ML projects in industry.

It would have been great to have few programming assignments included as well.

por Leonid M

Oct 05, 2017

Some tips are very useful for practitioners but the same information is repeated over and over again that makes the course quite boring.

por 김진수

Feb 26, 2019

I think this lecture is very useful when we make our own ML system.

Also, it has many examples about errors we can usually meet in real.

por Tim S

Feb 26, 2018

Useful, practical material. I probably underappreciate the importance of someone (especially of Dr. Ng's stature) covering this for us.