Chevron Left
Back to Structuring Machine Learning Projects

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

4.8
stars
49,915 ratings

About the Course

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

ED

Aug 22, 2020

Excellent start for digging into topics that are not taught nowhere else. The author books 'Machine Learning Yearning' is a great next read that goes deeper in some of the aspects, really recommended.

AM

Nov 22, 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.

Filter by:

5651 - 5675 of 5,723 Reviews for Structuring Machine Learning Projects

By David L

•

May 22, 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 7, 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 I

•

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 23, 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 3, 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 Iscru-Togan C T

•

Dec 12, 2020

The videos are to long and it presents some topics purely hipothetical. You basically spend a couple of hours without developing any useful skill

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 Stephen E

•

Jul 30, 2022

The quiz questions were often vague enough that it was easy to justify wrong answers using specific reasoning from the lessons.

By BO F

•

Jan 14, 2022

The exam's some question aren't consisted in the course. It's a bad learning experience compared with the previous two course.

By Matías L M

•

Oct 29, 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 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 4, 2020

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

By Peter E

•

May 2, 2018

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