SM
14. Juni 2020
A very deep and comprehensive course for learning some of the core fundamentals of Machine Learning. Can get a bit frustrating at times because of numerous assignments :P but a fun thing overall :)
SS
15. Okt. 2016
Hats off to the team who put the course together! Prof Guestrin is a great teacher. The course gave me in-depth knowledge regarding classification and the math and intuition behind it. It was fun!
von Francesco
•15. Nov. 2019
The material is good, but the choice of using GraphLab Create is a poor one. It's not used in the industry and it's poorly supported. I had issues installing it both via command line and via the installer, so I ended up using the AWS machine. But that has it's own drawbacks, such as the slowness and the setup time.
von Nitzan O
•25. Apr. 2016
The course is interesting and well taught. The professor is very enthusiastic and it makes the course fun to watch. The problem in my opinion is that the content is too superficial. It's completely lack of mathematical background and the programming exercises are sometimes no more than copy paste.
von ANIMESH M
•4. Sep. 2020
The course is up to the mark but what i felt missing is about the coding . They didn't focus on implementation tasks simply gave the notebooks for the assignments.
Also S.V.M and random forest classifiers are missing.
From my side concluding all the experience , i will give a 6.5 out of 10.
von Kumar B
•4. Okt. 2017
This course covers the basics of classification very well, but I would have liked optional sections on more advanced topics. Some of the quiz questions were a bit confusing. It would have been good if the exercises also dealt with unbalanced data sets in more detail.
von Neelkanth S M
•8. Apr. 2019
The content is good but completing assignments is a real pain because they choose to deploy a unstable proprietary python library, which gives hard time installing and running (as of Q1 2019). The entire learning experience is marred by this Graphlab python library.
von D B
•13. Juni 2018
Pros: Absolutely fantastic theory explanations. Establishes solid fundamentals. Cons: The bugs in test/notebooks could have not been rectified with new ones. Demands searching in discussion forum every time. Would highly recommend for starters!
von Eric A J C
•5. Aug. 2021
The videos were excellent, and the extra material to delve in deeper in the subject were very nice. However, the programming assignments were mostly chunks of ready-made code, so not much is left to the learner.
von ANGELICA D C
•22. Sep. 2020
Finalizo siendo muy confuso. El conocimiento de los videos opcionales no se le daba seguimiento, hasta el final en las tareas es cuando se usaba pero ya estaba fuera de contexto y era difÃcil entender.
von Supharerk T
•6. Juli 2016
All of the courses lecture are great until it reaches week 5 where it's really hard to catch, the programming assignment doesn't give enough hints and lecture in this topic doesn't help much.
von nazar p
•29. Juni 2017
While courses 1 and 2 of this specialization were quite good, I find this one a bit sparse on content. I think this course could be easily compressed into 2-3 weeks instead of 7.
von Rohit J
•12. Mai 2016
A lot of interesting parts of the course are available as optional and a lot of the difficult parts of the coding exercises are provided to you - the challenge is not there. :/
von Ilan S
•23. Nov. 2016
The videos were pretty goods. But a bit too slow and easy. The assigments were ok, but too guiding. Also there were too much reimplementation of algorithm
von Rahul S
•17. Juni 2020
Too much confusion, I face too much problem with this course. much confusion if you use different packages like sklearn.
von Lawrence G
•19. Mai 2016
The course content seemed to be rushed out, as a result, the quality is not as good as the first two.
von Tu L
•27. Juni 2018
Why don't you guys talk about ID3 or CART algorithm at all? This one is too basic.
von Mounir
•19. Juni 2016
Exercises for Scikit-learn users were not organised.
Course took too long to start
von Pier L L
•26. März 2017
Nice course but I would have expected more techniques (SVM for instance)
von Dmitri B
•6. Juni 2017
Theory Quizes are good, but programming assignment not so good for me.
von Ashish C
•31. März 2019
more topics like deep learning, neural networks need to be introduced
von Matt T
•12. Apr. 2016
Good, but overemphasizes niche software product (graphlab).
von Virgil P
•18. Feb. 2018
The exercises/assignments are far too simple
von 陈弘毅
•3. Feb. 2018
too simple
von Deleted A
•13. Aug. 2020
good
von Omkar v D
•14. Aug. 2018
.
von Rohan G L
•29. Aug. 2020
I leave 2 stars as I learned a lot of new information and methods, and the theory and math behind them.
You will learn about Data Science and Machine Learning, but not much about Python.
The course is pretty much abandoned and outdated. Sframes and Turicreate packages (instructor's creations) are used instead of more universal packages. Installation in the beginning took some time and research. Many of the assignments have errors and bugs in the code that have not been updated. Forum assistance is abysmal for clarification or deeper questions. Many links are dead.
There are many times in the lectures where the instructors are writing several sentences in their handwriting on their notes instead of having the text ready to appear.
I would suggest using this course and series as a supplement to other information one as learned, not as an introduction for initial understanding. I found myself frustrated too many times.