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미시건 대학교의 Applied Machine Learning in Python 학습자 리뷰 및 피드백

4.6
별점
8,018개의 평가
1,463개의 리뷰

강좌 소개

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models will be described, and learners will be able to apply the scikit learn predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting). The course will end with a look at more advanced techniques, such as building ensembles, and practical limitations of predictive models. By the end of this course, students will be able to identify the difference between a supervised (classification) and unsupervised (clustering) technique, identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write python code to carry out an analysis. This course should be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python and before Applied Text Mining in Python and Applied Social Analysis in Python....

최상위 리뷰

OA

2017년 9월 8일

This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses

FL

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!!

필터링 기준:

Applied Machine Learning in Python의 1,454개 리뷰 중 76~100

교육 기관: Dr. S I

2022년 4월 24일

Course was good but It became very tough, because me and other students are facing a lot of problems and errors in assignment submission. Submission of assignement is not clean as it should be. please update and remove errors we are facing during the submission of the the assignment.

교육 기관: Ankur P

2019년 3월 30일

Unsupervised learning was missing. The codes written in the lectures were not explained clearly. Some topics looked unimportant.

교육 기관: James F

2018년 2월 13일

Good overview of methods. A bit too intense at times though, may have been better to really focus on a couple of key concepts.

교육 기관: Choi H

2018년 11월 22일

어려웠어요 ㅠㅠ

교육 기관: Katherine F

2020년 10월 28일

This is an incredibly dry course from the University of Michigan. In typical academic fashion, it churns out a bunch of lectures, expects you to remember the content, then throws you straight into some quite complicated problems. Half the time, these problems don't even work and you have to dive into the forums to find out how to correct mistakes that the content providers have failed to correct themselves, even several years down the line. There are iPython notebooks you can use to follow along with the lectures, but really they could do with useful information and explanation embedded within them, which is one of the main strengths of iPython notebooks and has been sorely underutilised here. If the course material were presented in a more interactive and engaging manner, the learner might be more motivated and engaged when solving assignment problems. As it is, unless you have prior knowledge or experience within the field, or a mountain load of free time, it's more an education in frustration than machine learning.

교육 기관: Justin F

2017년 9월 26일

The quality of this course in the series is a far cry from that of module 1 and 2, which is a shame because this is the one that I was really looking forward to. The professor does not seem comfortable and uses a lot of extra words in his lectures which can make them confusing and rambling. Many questions on the quizzes and assignments are not covered or well explained by the material. Many assignment questions have to be explained by teaching staff on the forums because the task is not clear.

교육 기관: Martin M

2020년 8월 10일

Week 1 was great...and then it all went downhill.

Too much material cramped into 4 weeks. The lectures are monotonous and rarely go in detail and provide real world cases. yeah, the data is from the real world but just punching code without explaining it is not very instructive.

Oh yeah, and lets not forget the last time the course has been updated was in 2017 and none of the bugs that keep popping up with the code and the autograder have been fixed.

교육 기관: KHADE R N

2020년 5월 9일

First two courses of specialization were so good, but I am disappointed by this one i.e. Machine leaning. I know this course is applied but then also advice for others, this is absolutely not for beginners, because there is too much rush in this one. I didn't understand 60% of things because new concepts are taught one after another without deep understanding and mathematical concepts that how it is working.

교육 기관: ALONSO A R P D A

2020년 7월 11일

Sorry by bad writting, english is my second language, but:

Again, the videos and suggested reads are not sufficient to learn all that is needed in assingments or in real life application. Doing others courses in coursera like courses offered offered by University of Macquaire turn more clear that this course is so hard to learn because there's less things that what is actually the subject

교육 기관: Gregory O

2017년 9월 25일

I was excited going into this course because the others in the series were taught well and I had learned a lot. Unfortunately, this course greatly disappointed. The lectures were dull, included a lot of mistakes, and did not cover most of what was expected during the assignments. All in all, this course was a waste of time versus just learning scikit-learn on your own.

교육 기관: Shubham N

2020년 8월 23일

Not happy & satisfied with the assignments. Whenever I tried to submit, always error occurs, mostly files does not exist. Went to forums though, but files are kept elsewhere, especially for Assignment 4. Had to specially download the file and uploaded in the project directory just to work. Need to have proper file arrangements before starting the assignment.

교육 기관: Nahuel V

2020년 8월 3일

I am not a big fan of this course. The assignments were too easy up to the last one that was too hard. There is no moderation in the forums, you can ask a question and nobody will answer.

교육 기관: Subhadeep B

2020년 8월 20일

The instructor makes me sleepy. The autograder runs outdated versions of many packages and was last updated in 2018. Although the mentors are always active in the discussions forums.

교육 기관: Thomas M S

2018년 2월 9일

I do not have the impression after this course that I have reached a level of familiarity that I will continue using the content of this course. Disappointing.

교육 기관: Dror L

2017년 11월 25일

great topic, poorly presented. material not well divided among weeks. lots of repetitions. lack of hands on practice until the very last task.

교육 기관: Kale H

2020년 5월 31일

Autograder is poor and professor is hard to listen to. You're better to just do a YouTube tutorial, like Codebasics.

교육 기관: Stephen O

2020년 8월 25일

Desperately in need of an update as much of the code is no longer up to date/broken.

교육 기관: Keshav B

2020년 1월 2일

Instructor tell the thing which are far beyond from asignments and quizes

교육 기관: Mohamed R

2020년 3월 27일

one of the worst courses i ever had

교육 기관: Frank A N

2018년 11월 19일

It was too easy

교육 기관: Will W

2021년 4월 24일

Maybe this was once a decent machine learning course, but clearly in the last several years its administrators have abandoned it, and it is now in a state of neglect. All the assignments have bugs and errors which are never fixed. There are hundreds of forum posts with students who are confused by these errors but most of them go unanswered. When a moderator does answer a post (this happens very sporadically because the course has "limited moderation" aka no one is helping students), its only to point out previous posts with work arounds to the bugs. All questions as to why these bugs aren't fixed, saving everyone untold amounts of trouble, are ignored. I don't know if anyone will see this as I suspect most reviews on this site are fake, but please do not take this course if you value your time or money, its creators no longer care about it and are using it as a money machine they can run without any effort or interaction with students. U of M should be ashamed to have their good name on this.

교육 기관: Jeff S

2021년 1월 1일

Impossible to complete the quiz and assignments without EXTENSIVE self-learning from other material. So, while the quiz and assignment forced me to find the information I needed by googling and reading and buying books, the course material itself is so high altitude as to be completely useless. I only finished because I used trial-and-error and google to pass. I learned nothing from the course, but I learned plenty from the Internet. I'm glad my company is paying for this and not me.

교육 기관: Rachit G

2020년 7월 30일

The instructor is very very boring

교육 기관: Deepalakshmi K

2019년 6월 19일

Dude

교육 기관: Kevin L

2017년 6월 24일

A great introduction to the practical side of machine learning, particularly if you have already taken Andrew Ng's course. It covers a *lot* of material and the pacing is *very* fast. Week 2 is particularly long, and if you are still a student/working it may take an extra week to complete the course. Quizzes and assignments are not terribly difficult, but be careful of the project assignment in Week 4 (though the bar for a 100% is quite low!). Finally, the accompanying Jupyter Notebooks are very helpful and there are many helpful links to outside resources as well.

A few of the lecture videos feel like an early draft rather than production-quality, with lots of time spent on repeating phrases. The instructor mentions things to be covered "later," but that "later" never comes (for example, in discussing Grid Search). For some background, this course appears to have been repeatedly delayed before its release. To me, is understandable that the creators wanted to get this course out given the demand, but the rush is felt.

Ultimately, however, this is still an excellent introduction to Python Machine Learning, and I do feel the course is well worth taking. Just be prepared to do some more individual learning; however, shouldn't one always be for an online class?)