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Отзывы учащихся о курсе Structuring Machine Learning Projects от партнера

Оценки: 48,142
Рецензии: 5,524

О курсе

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....

Лучшие рецензии


1 дек. 2020 г.

I learned so many things in this module. I learned that how to do error analysis and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.


1 июля 2020 г.

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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5426–5450 из 5,491 отзывов о курсе Structuring Machine Learning Projects

автор: Leonardo M R

27 мая 2018 г.

Answers in the multiple choice seems incomplete for me, I don't necessary agree with the answers presented unless more detail on some context (that I don't think we should assume) is present for the questions.

автор: Пильгуй В Л

3 дек. 2019 г.

This course is good, but here is so few practice. This is hard to understand without practice. Looks like I didn't understand many problems in this course. Need more explanation, more samples, more practice.

автор: David L

22 мая 2018 г.

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.

автор: Mahesh B K

30 апр. 2020 г.

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

автор: Nikolay B

26 окт. 2017 г.

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.

автор: Bradley D

15 июня 2019 г.

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.

автор: Matthew J C

7 мар. 2018 г.

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.

автор: John H I

21 сент. 2018 г.

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.

автор: Aayush S

19 июля 2020 г.

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.

автор: Mikael B

13 сент. 2017 г.

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.

автор: Artem M

23 апр. 2018 г.

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.

автор: Haim K

3 июля 2020 г.

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.

автор: Iscru-Togan C T

12 дек. 2020 г.

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

автор: everglow

27 янв. 2019 г.

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!

автор: Saad K

12 сент. 2017 г.

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

автор: BO F

14 янв. 2022 г.

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

автор: Matías L M

29 окт. 2017 г.

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

автор: kedar p

18 июля 2018 г.

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

автор: Viliam R

21 окт. 2017 г.

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

автор: Vishal K

17 дек. 2017 г.

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

автор: Benoit D

15 авг. 2017 г.

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

автор: Mads E H

26 окт. 2017 г.

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

автор: Dafydd S

23 окт. 2017 г.

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

автор: Alexander V

25 февр. 2018 г.

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

автор: Nahuel S R

4 мар. 2020 г.

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