2017년 10월 13일
Very well structured course, and very interesting too! Has made me want to pursue a career in machine learning. I originally just wanted to learn to program, without true goal, now I have one thanks!!
2020년 11월 26일
great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.
교육 기관: Rakesh D•
2019년 11월 10일
lectures are boring, not updated but yes i learned something, but its not up to the margin
교육 기관: Robert S•
2020년 6월 11일
I had high hopes going into this course after the really well put together courses 1 and 2 in the specialisation, however the video material was dull and disengaging. Where the lecturer could have spend hours going into the ins and outs of how the different algorithms work, instead the course followed a structure of: 1 - Brief overview of an algorithm, 2 - whats the syntax in scikit-learn, 3 - what parameters does it take, 4 - what other commands are there
I was really disappointed, as most of the actual learning was done from reading other sources on the web and watching videos for free on YouTube. I guess the only positive is that because I paid for it I was forced to finish it?
교육 기관: Karim F•
2020년 7월 10일
worst course of this specialization so far , the instructor is just reading stuff not making any effort whatsoever and it seems like he's obliged to do teach this course ,the autograder is the worst and the journey with this course is really painful i hope that you take these points in consideration and just delete this course
교육 기관: Yuchen P•
2017년 10월 9일
The materials of this course is poorly arranged: how is that even possible to cover gradient boosting, random forest, neural network, and unsupervise learning in a single week?
교육 기관: marcos r•
2018년 11월 6일
This is a really bad quality course. A little bit more professionalism would be advisable. I will continue to the next course and leave this behind.
교육 기관: Rezoanoor/CS/Rezoanoor R•
2020년 3월 21일
Faced problem in every assignment while reading the data sets. If the data is not in that folder what is the point of telling so?
교육 기관: Omid•
2018년 9월 22일
1- very slow paced lectures
2- very basic and elementary examples
To sum up, it is boring and not useful for practical application.
교육 기관: Sandeep S•
2019년 11월 24일
I am not happy with the course material and the way teachers are teaching.
교육 기관: Abbas S•
2020년 9월 10일
This is not a good course for beginners.
교육 기관: kapish s•
2019년 5월 28일
no teacher intraction
교육 기관: NoneLand•
2018년 1월 21일
A very practical course for machine learning. By this course, one can get familiar with sklearn and pandas basic operation! The last assignment is a challenge for me. Thanks teacher for this great course!
교육 기관: Alan H•
2019년 5월 8일
Great course for the applications of machine learning. While I wouldn't recommend for someone with no ML experience, this was a great course for an R user trying to learn more python!
교육 기관: Rami A T•
2017년 6월 6일
Very helpful and well-structured course, clear lecturing, and high-level assignments. I hope, however, if it can be offered another course specialized in unsupervised learning in ML.
교육 기관: RAQUIB S•
2020년 5월 5일
Great Course. I love the way it is designed, delivered. I learned a lot. The most important part is that I enjoy every bit of the session and completed everything less than a week,
교육 기관: Ravi M•
2020년 2월 8일
Course was designed in a well structured manner and the basic concepts were covered for Regression and Classification. Many many thanks to University of Michigan for creating it.
교육 기관: Malvik P•
2019년 10월 30일
The course is awesome. Professor Kevyn Collins Thompson, explains the topics with examples in python which makes content easy to understand. It is the best course for beginners.
교육 기관: vishy d•
2017년 8월 6일
It is very good blend of study and practical assignment. Assignments were very well designed to greatly enhance the understanding about the things learned in the video lectures.
교육 기관: Rob N•
2017년 10월 14일
This course was challenging and extremely interesting. The long and detailed lectures and excellent lecture notes covered the material very thoroughly for an online course.
교육 기관: Karthick T J•
2020년 7월 17일
ML is a wonderful course.I learn new concepts with hands on experience.Each and every algorithm concept is clearly explained .I learn how to handle real time data set.
교육 기관: Raga•
2017년 6월 9일
Very well designed courses! There are many materials to go in depth even if you have done Python Machine Learning in the past.
교육 기관: Eduardo L L•
2021년 11월 12일
It's a really good course. I teaches you the basics of many ML algorithms. I really recommend it for begginers
교육 기관: Jun-Hoe L•
2020년 6월 3일
My actual rating is 3.5 stars. This is the best course yet in this Specialization.
Pros: I prefer Professor Collin-Thompson's delivery compared to Professor Brook in the previous modules. I think he gives a good overview and sufficient depth for an applied course, compared to Professor Brooks which I find to be quite superficial most of the time, and weirdly detailed in other parts. Assignment is good enough for reinforcement learning and definitely better planned. I also appreciate the link to additional readings which are quite informative.
Cons: Assignment auto-grader. This is still the biggest letdown of all the courses in this specialization Codes which work on your laptop or suggested elsewhere on Stackoverflow etc fails to pass the autograder, so 30-40% of the time of the assignment is spent on wrangling the code to pass the autograder.
Note: If i haven't taken a Machine Learning course by Professor Andrew Ng, this course would definitely be much harder. This course doesn't go to much into the background knowledge,and they mentioned this many times. But I appreciated the applied aspect, since this was what I was looking for.
교육 기관: Oliverio J S J•
2018년 2월 4일
This course is an survey on how to implement many machine learning techniques using the SciKit Learn library. Following the course, you can learn several interesting details about how to work in the field, but it is important to take into account that it is not possible to learn the algorithms during the course, since a huge amount of material is covered during a short time; to make the most of the course you have to know them in advance. It bothered me to discover that the course was planned for five weeks but Coursera has reduced it to four, removing the possibility of practicing exercises on unsupervised learning.
교육 기관: Andrew B•
2021년 3월 24일
Overall a good course; I learned a lot. But hard going at times for someone new to Python and Jupiter Notebooks. The time estimates for the module assessments are way under (maybe reasonable if you are already a Python expert and have some familiarity with the relevant libraries, but that's not my situation). File location mismatch between Assignment notebooks environment and submission / assessment environment was very frustrating.
교육 기관: Raivis J•
2018년 7월 27일
Since there are many theoretical concepts in this course, like model evaluation and tuning parameters, it would be much better if those are explained using real or semi-real life problem examples. Especially the quizzes needed more context as to why a particular situatrion might occur, and why that particular variable of interest is necessary.