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Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI

4.8
stars
44,204 ratings
4,985 reviews

About the Course

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....

Top reviews

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.

JB

Jul 02, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

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4876 - 4900 of 4,935 Reviews for Structuring Machine Learning Projects

By David L

May 23, 2018

Zero programming assignments, but simple quizzes that will make whatever you just learned as fleeting as the morning dew on a hot summer's day. Too bad, because otherwise the material is quite interesting.

By Mahesh B K

Apr 30, 2020

Although important, i think this should be the last course in the specialisation as it covers the harder parts of handling various errors and their causes before knowing how these models are trained

By Nikolay B

Oct 26, 2017

the best course in so far, not that much theory but a lot of "insides" from the field. However, still no practice, Im studying for 3 month and still have no idea how to create a real application.

By Bradley D

Jun 15, 2019

There's theory, but, without practice and application in my opinion. I did not like it because it seems to be easily forgotten seeing that I did not associate with practical excercises.

By Matthew J C

Mar 07, 2018

Most (if not all) of the information covered in this module was covered, perhaps with a little less depth, in the previous modules. However, it's probably worth repeating.

By John H

Sep 21, 2018

Poor video editing. Not enough graded material to feel confident that I fully understand the concepts proposed in the lectures. Definite step backwards from courses 1-2.

By Aayush S

Jul 19, 2020

Could be better in terms of the concept taught. A course I would prefer as the last one in the specialization. Week 2 Material is good but whole course is too slow.

By Mikael B

Sep 13, 2017

This course had a much less ambitious scope than the previous two courses and I think that the programming assignments are very important to help me learn properly.

By Artem M

Apr 24, 2018

Too much information in too little time. Additionally, all information is mostly practical, and having no real exercises makes it hard to remember all the details.

By Haim K

Jul 03, 2020

The course should be much shorter (e.g. half a week). The messages are pretty straightforward and could have been passed in one quarter of the time.

By everglow

Jan 27, 2019

I still feel a little confused when I have so many options to improve my NN. This course is less clearly taught than the two former to this one!

By Saad K

Sep 12, 2017

I found it quite verbose... Could have easily been shrunk and fit inside the other course... Don't think it needs a separate course for this

By Matías L M

Oct 30, 2017

Really bad course. Even the professor does a good job at explaining everything, it does not seem to be a technical course :(

By Kedar A P

Jul 18, 2018

This course is too theoretical, would like to see some multi task learning or transfer learning programming assignments.

By Viliam R

Oct 21, 2017

i missed practical (programming) assignments here. quizes are great, but could never substitute for getting hands dirty.

By Vishal K

Dec 17, 2017

The weakest of the three so far - comparatively lots of fluff. Unclear definitions with lots of perhapses and maybes.

By Benoit D

Aug 15, 2017

I have been working in industry for 5 years now and this are not really the problems we encounter in practice.

By Mads E H

Oct 26, 2017

Not applicable enough. I think you need more tooling around DL before these meta lectures makes sense.

By Dafydd S

Oct 23, 2017

Had the feeling of a "filler" course although it was interesting to hear about the various challenges

By Alexander V

Feb 25, 2018

A lot of very common-place suggestions that could just as easily be conveyed in a third of the time.

By Nahuel S R

Mar 04, 2020

Demasiado contenido teórico sin aplicaciones prácticas reales que permitan consolidar lo aprendido

By Peter E

May 02, 2018

Too theoretical. It would be good to have some practical (programming) assignments here as well.

By Mohamed E

Nov 23, 2017

Not much to learn in this course, basic recommendations can be condensed in one or two lectures

By Jordi T A

Aug 28, 2017

A lot of the content seemed redundant both within the lectures and with the previous courses

By Clement K

May 11, 2020

Interesting but redundant. It's not worth an entire course, even if it's only two weeks