워싱턴 대학교의 Machine Learning Foundations: A Case Study Approach 학습자 리뷰 및 피드백

Course contet is ok. But, intructors really need to teach in a platform neutral way or some other popular library for which ample support is available. In my opinion, learning a tool which is nowhere used in te industry is not a good idea.

the course is good for starter but according to its repetition I waited more .

one star down for many useless information in lectures about Amazon products and so on.

one star down for forcing using unpopular python library .

thanks to prof and cousera for this wonderful course. I wish the programming part was taught separately from basic. I have taken the previous course which was case study approach with respect to which it was slightly tough.

The teachers are nice and the content is pretty interesting, but they keep talking about the Capstone that we actually won't do. That make me wonder if it's worth continuing, and wonder why they cancelled it eventually.

This was a valuable introductory survey course. For me, the challenge came from my unfamiliarity with Python not the material. I would rate this class as "entry level" for anybody with a college-level technical degree.

There were a lot of assumptions made about my math background. Terms and concepts were used that are foreign to most people and while the forums were helpful it was interesting to see that this is a common feeling.

Course include great knowledge, but when coming to work on tools, they are using old method like we have python 3.7, but course is going through python 2.7 and also older version. That's creating confusion somehow

It's not a bad course, but it forces students to use GraphLab, a framework created by one the professors teaching the course, instead of using scikit-learn, a widely used framework for machine learning in Python.

This course has so much potential but is based on proprietary software. The instructors are excellent and the content is really good. It would get 5 stars if it was based on all open source software.

Great approach with basic explanation of applying and importance of the domain in read world examples. Could have been more in depth in few areas but hopefully will be taken care in following courses.

The course needs to be updated....I have hard times installing turicreate and graphlab on my laptop... at the end, I had to use google collab....

I guess this course needs to use tensorflow instead...

Aprendí muchas cosas interesantes. Actualmente es grande la dificultad para realizar las prácticas de programación con la librería que usan "graphlab" la cual no se relaciona my bien con windows.

In and of itself, the content of the course was pretty good. However, after working through 2 deep dive AI courses of each 6 months, obviously this particular course was not much of a challenge.

The Professors and the lectures were excellent. Homeworks are way to easy. Would like to use open source tools like pandas and sci-kit learn instead of proprietary tools like graphlab.

I cannot download all the software needed specifically Turicreate, despite the provided link it shows never-ending errors, after a week of trying I had to give up the course since.

This course needs to be updated. It's hard to follow the notebooks since the lecture was on GraphLab, and some of the explanations were not elaborate enough, especially Week 6.

I like more to work with sklearn rather than GraphLab..

Actually many recommended this course to me, and I expect more excitement in the next courses in this specialization

Pros : You will get a great fundamental conceptual understanding of basic ML concepts and practical implementations.

Cons: Using Turicreate over sci-kit learn and tensorflow

I don't like this course , because the homework can not match the lesson. I can not got more messages to completed the homework.

So I will Unregister this courser , Thanks.

The only reason that I am giving 3 star is the design of the quizzes for each week. The readings are too long and the content of the quiz sometimes gets you frustrated!

Professors are very good , i am really enjoy in this class, but no further discussion about implementing ML algorithm, just call the API to handle the sort of data.

The lectures are fine. However the content is way too easy. Another course on Coursera `Mining Massive DataSets` is much better, in the depth and horizon.

App needed to complete assignments ceased to function early on - forum / admin did not help to find solution. Otherwise good intro to get started with ML.

Generally ok. Towards the end of the course, the lectures could have been a bit more in depth - or provide students with a more in depth reading list.

I think this is an excellent course. I would have given 5 stars if this course is not based on Graphlab which is not affordable to the general public.