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

4.8
31,213 classificações
3,281 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.

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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3151 — 3175 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Andrej P

Jan 26, 2018

I found this course to be a bit confusing with regards to what data set (training/dev/test) to fix under what conditions and so on. I've also missed having a practical home work, the case studies were fine, but I find that practical applications help me remember things better.

por Giacomo A

Jan 28, 2018

Contains some useful tips, but they are a bit too diluted - I feel like it could have lasted much less and still conveyed the same information.

por Manish S

Apr 09, 2018

Content was not enough to create a new course.

por Srikanth C

Aug 28, 2017

This course offers some good advice when it comes to (much needed) practical considerations when training neural networks, and to a reasonable extent machine learning algorithms in general. I personally don't see myself successfully applying the content on Multitask Learning, Transfer Learning and End-to-End ML in real scenarios straight after finishing this course unless I go ahead and learn these in more depth. The "flight simulator" approach to applying what has been taught was great! I would have liked more (perhaps optional) exercises in this format. I would have also not minded a longer course that could go more in depth into the bias-variance tradeoff and the aforementioned topics.

por Pratik k c

Nov 05, 2017

Very Theoretical !!

por Karthik R

Mar 04, 2018

Transfer Learning and Multi-Task learning discussed in the course would greatly benefit from having programming assignments where people can play around with the data and learn confidently.

por Francisco S R

Oct 25, 2017

The course was just a bunch of tips and suggestions. Yes, they are useful, but given the empirical nature of machine learning I would expect those tips to be accompanied by practical applications and homework.

por Francesc C F

Aug 28, 2017

I missed the coding parts

por Martín A B

Oct 24, 2017

The curse is quite simple, there are a few interesting insights so it's not all bad. I feel I've learnt some interesting ideas. However, I feel it's quite incomplete. There are several problems that happen "in the wild" that are not covered. There is more that image classification and speech recognition to machine learning, therefore the experience of Andrew makes the course content biased to problems that are interesting but very specific. I was expecting something better given the quality of the first ML course.

por Yan W

Oct 24, 2017

Expect more hand-on code practice or more quiz

por Rob W

May 12, 2018

Seemed to be information that could have been included in another course rather than its own 2 week course.

por Kevin Q

Mar 19, 2018

lot of issues with assignments and ambiguous quiz questions this time around, not as polished as other Andrew courses

por Arghya R

Sep 19, 2017

Could have more case studies and above all. Also programing assignments on self driving car could have been better

por Benedict B

Jul 27, 2018

ich

por Isaraparb L

Jul 15, 2018

The early part rather feels slow and repetitive. The course's content seems very important though.

por Mustafa H

Jul 17, 2018

This course does discuss interesting and important subjects but I feel it can be combined with course 2 of this series

por Ahmed A

Jul 10, 2018

course is very good have a lot of important theory, it will be amazing if become 3 weeks with programming assignments.

por kritika

Mar 26, 2019

I think the week 1 was overstreched. There was not much content to deliver and for the first time Andrew's classes made me sleep. It was like the boring lectures we get at school. I think we can easily shorten the length of this course or just scrape it and add it to course 2.

por 成文辉

Mar 27, 2019

programming assignment is needed.

por Mats B

Mar 30, 2019

This course did not really feel like a course, just videos and ambiguous quizzes. Some repetition and poor editing of the videos. I recommend to reformat this course to be more substantial and to include programming exercises.

por Tzushuan W

Jun 01, 2019

Wordy and too abstract without hands on experience.

por Janet C

Jun 29, 2019

Overview of the machine learning process. No projects or sample code to actually organize the ideas into code.

por Nicolas

Jul 09, 2019

not as interesting as the other courses

por Abhijeet M

Jul 07, 2019

Informative but too short

por Diego P

Jul 12, 2019

Videos are quite long. Good course although a bit heavier than the previous ones