Mar 01, 2017
Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.
Jun 18, 2018
Excellent introduction to basic ML techniques. A lot of material covered in a short period of time! I will definitely seek more advanced training out of the inspiration provided by this class.
创建者 Jeffrey G•
Sep 12, 2017
Course project was the only project work, needed more. This course should also use swirl(). Quizzes et al contained mistakes.
创建者 Michael R•
Oct 03, 2019
It's a mediocre intro to some machine learning tools. I think the course materials could be drastically improved.
创建者 Philip E W J•
Jan 30, 2019
Jef leek explains to fast and the theory behind the different algorithms is scarcely explained.
创建者 Allister G A•
Dec 25, 2017
The course needs to elaborate more on hands on discussions.
Jan 18, 2017
not what I expected for a machine learning course
创建者 Y. B•
Feb 06, 2016
incomplete and not clear. extremely disappointed.
创建者 Yang L•
Aug 14, 2016
needs more case studies and examples
创建者 Haolei F•
Mar 13, 2016
Need to get more in-depth
创建者 Gianluca M•
Oct 20, 2016
Gosh I hated hated hated this course. Nothing to learn here. You will just be given lots of names with no explanation whatsoever.
I often felt really angry at the teacher because of the way he would introduce entire prediction models without explaining anything about them. Also, I really didn't like the fact that the course is centered on caret, a "shortcut" package to do stuff fast. Before doing things fast I need to know what I am doing! Finally, the quizzes and assignments are completely disconnected from the courses.
The worst course I have ever taken on coursera.
创建者 José M M A•
May 25, 2020
This course did not fulfill my expectations. It is the worst one in the Data Science Specialization by far.
Although the explanations are fine, sometimes they are too vague and there is no practice at all, when the title of the course is "Practical".
Most of the tools used are not comprehensively detailed and the quizzes are quite confusing.
Some of my peers reported that the course is not updated since 2013, which is a severe flaw when talking about one of the statistical tools more in-fashion nowadays.
创建者 Ricardo G C•
Jun 17, 2020
The professors are experts on the subject, but unfortunately they rush through content and some of the classes are outdated (i.e. they use packages and data that are not the newest version) and this generates confusion througout the course.
创建者 Danielle S•
Mar 22, 2016
Material is very high level. No ppt's are given, so all links presented in the video's cannot be viewed.
Quizzes are based upon old packages, so incorrect answers are provided.
No replies at discussion board from TA"s or instructors.
创建者 Jo S•
Feb 04, 2016
Poor compared with some of the others on this specialisation. The lectures are too fast and high level, with no allowance given for people who are unfamiliar with this area and attempting to learn it.
创建者 Robert O•
Apr 06, 2016
Very little depth. I don't recommend this if you don't already have background in statistics or R. I really didn't learn anything. I mostly just gamed the quizzes and projects.
创建者 Etienne B•
Mar 01, 2016
Cannot take the exam, I have to pay... wtf... I will probably pay at the end, but I want to take the class first. Without certificate I cannot prove I took the course.
创建者 Eduardo S B•
Jan 26, 2020
They explain nothing on the fundamentals of the machine-learning methods, nor how to know which method apply to a given problem.
创建者 Abhilash R N•
Dec 04, 2019
This course is NOT for the beginner. Take time to finish all the beginner and foundation courses and then take time to learn R
创建者 Emily S A•
May 25, 2020
In my opiion, this course needs to be improved a lot. There are almost nothing Practical Machine Learning.
创建者 yi s•
Jul 19, 2016
too general no depth, not recommended for science or engineering degree holders
创建者 Stephen E•
Jun 27, 2016
To be honest I don't think this is worth the money.
创建者 Stephane T•
Jan 31, 2016
Too much surface, not enough depth.