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

4.8
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35,191 classificações
3,679 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

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.

DC

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!

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3201 — 3225 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Abhinand

Mar 28, 2019

The answers to the questions in the Quiz are ambiguous and subjective.

por Wynand

Feb 15, 2018

Good, not dissimilar information from what was taught in the ML course

por R. P R

Nov 30, 2017

Will return to this lecture again in the future as reference material.

por Isaac K

Nov 27, 2017

Has some useful information, but is lacking any programming exercises.

por george v

Nov 02, 2017

great-practical advices. nice simulation of the problems in the quizes

por Tianyue Z

Sep 11, 2017

Talks about error analysis and strategies of how to proceed a project.

por Abhishek N

Dec 23, 2018

Great course. Loved the lectures, but the assignments were ambiguous.

por Jesús C

Oct 13, 2018

Great course!

I only missed how to deal with unbalanced training sets.

por Jeremy O

Jul 14, 2018

Great information - A few more video errors than in previous courses.

por John W

Oct 02, 2017

Another informative course. A bit repetitive but overall very useful.

por Jacques J

Sep 06, 2017

Would have loved a lot more content and a lot more practice examples.

por Edoardo S

Feb 02, 2019

A bit too theoretical and not empirical but still really interesting

por Michael B

Apr 04, 2018

Well structured material - trigger the desire to know more and more

por yifeng z

Feb 27, 2018

kind of lacking in practical assignment. only quiz seems not enough

por Roger F

Dec 04, 2017

It would be great to get some explanations in regard to both tests.

por Shirley Z

Nov 06, 2017

Could be more examples or coding assignments for transfer learning.

por Chao L

Sep 29, 2017

Distills the key and practical aspects of machine learning projects

por Tomas O H

Jun 20, 2019

Very useful intuitions, needs a little more of coding if possible.

por Aniceto P M

Apr 24, 2019

This course is a bit short but there i a lot of experience bottled

por Javier F P V

Oct 19, 2017

Programming assignments for transfer learning would have been nice

por Manish C

Jan 29, 2020

Nice to learn skills about project handling in machine learning.

por Luis E G

Dec 23, 2019

A little bit boring and repeated info., but still valuable stuff.

por Lili W

Aug 20, 2018

Tooo much time to repeat boring things...but still a good lesson!

por Nicholas K

May 14, 2018

Worthwhile: good info and the practical aspects of tuning models.

por Alexander Y B

Apr 24, 2018

Good for understand how to spend your time on DL projects I guess