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學生對 IBM 提供的 使用 Python 进行机器学习 的評價和反饋

4.7
9,949 個評分
1,637 條評論

課程概述

This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed! By just putting in a few hours a week for the next few weeks, this is what you’ll get. 1) New skills to add to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 2) New projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more. 3) And a certificate in machine learning to prove your competency, and share it anywhere you like online or offline, such as LinkedIn profiles and social media. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course....

熱門審閱

FO

Oct 09, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

RC

Feb 07, 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

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1551 - 使用 Python 进行机器学习 的 1575 個評論(共 1,621 個)

創建者 Rao M H

Apr 01, 2020

Lab are working worst

創建者 Rajesh K R

Dec 12, 2019

Good for beginners

創建者 Сокол С А

Dec 02, 2019

Too superficial

創建者 Akash S D

Aug 20, 2020

Good

創建者 Farrukh N A

Jul 15, 2020

I have just completed the course and mentioned below are my key pros and cons for this course:

Pros:

1) I loved the theory and different techniques explained in the course.

2) The presentations were very well made and it helped me to gain knowledge as far as ML is concerned.

Cons:

1) This is a pretty outdated course, where there are ALOT of typos and coding errors throughout the labs as the coder has left IBM and is working in some other company for more than a year now. Thats is why no one is there to update the course.

2) The title of the course should be "Machine Learning with Mathematics" rather than "MAchine Learning with Python" because the emphasis of this course is on using mathematics to solve ML related problems and that is why most of the libraries and techniques used in the python files were not defined.

3) This IBM's specialization is of BEGINNER level and the inclusion of an INTERMEDIATE level course which requires you have to have some experience in Data Science and advanced level knowledge of Python is just mind boggling to me. It would have been great if a basic level course of ML would have been developed which emphasized on explaining while using Python libraries would have been much more appropriate for us.

4) Lastly, it has confused me while going through this course that numerous times the lecturer spent major time of the lecture in explaining the advanced mathematics which Pythons libraries can easily do for you, even if he told us that remembering of the mathematics is not need. STILL he explained it. I don't know why he did it again and again.

創建者 Lyn S

Aug 23, 2019

It's too bad some people with phds and very poor teaching skills think they can write up some code and feel they are teaching these classes. That being said, it's super cheap and it's very easy to find information online to supplement the lack of adequate descriptions of the topics. Changes that would make me more likely to take another coursera class :

Don't have a bunch of really short videos, combine them into one longer one.

If there is text or code on a slide, make sure that is in the transcription.

Don't have the dumb popup questions that stop the video and make you find the mouse and click to restart the video. Many of us are listening to the video doing something else, I listen over and over. Sometimes, I have to read the transcription to understand what is being said, so I have to stop, get the mouse, click back up to the slides, press SKIP, etc...

If you have an exam, make sure to later send us the answers - e.g. the code that we were expected to write. This is the weakest and most frustrating part of this class. I was not sure how to some things, in part because I wasn't sure what was being asked, to what detail. Even the class discussions showed we weren't sure what data set to use for what. It seems to rely on peer grading, but most of the responses I got from peers was either completely absent or not useful. But thanks for keeping this relatively cheap.

創建者 Fangfang K

May 17, 2020

I learned a lot from this course. However, had I known what I had to go through to learn the knowledge, I would not have taken the course; the process is too painful. Therefore I would not recommend the course to future learners. Read my review and save yourself $39.

1) Too many typos, bugs, inconsistencies throughout the videos and labs. The same mistakes have been brought up by students over and over again on the discussion forum, but have never been fixed.

2) Teaching staff do not pay attention to students asking for help. Sometimes when they do answer the question, they give a very vague or irrelevant answer; and when being pointed out by students that their answer is not helpful, the teaching staff do not bother to reply and address the issue. I feel like the teaching staff never went through the entire course themselves so they do not understand our students' concern and frustration.

3) A lot of Python codes are never explained or commented. This is a beginner level class but they expect you to be able to code proficiently; otherwise you are going to be stuck with one line of unexplained code for a long time...

4) The whole course is like a giant advertisement for IBM Cloud, which is not user-friendly at all.

創建者 Miranda C

Aug 22, 2020

At first this class seemed easy to follow, but that was deceptive. While I learned some theory (and some mathematics) behind the algorithms we were meant to learn, there was far too little emphasis on how and when to run the actual code. Normally the labs are a helpful part of these courses, wherein I have the opportunity to actually learn code. Not so with this course.

When I reached the final project for this class, I had no clue how to do what we were supposed to do, as essentially, it had not been taught within the course. I had to seek out other sources in order to actually learn the material and make a lot of educated guesses about what I was suppose to do. I suspect (or hope) that much of this will become easier when I re-take Statistics and some other maths (not course requirements), but that won't make up for the deficiencies in the course. Lastly, the typos and other grammatical errors are extremely distracting and misleading (i.e. "lables" -- do they mean "tables" or "labels"? Who can say for sure!).

創建者 Tom S

May 13, 2020

Like many of the courses, the instructions are not in a format that supports incremental learning and focuses on the mechanics for performing an activity rather than an explanation for why and the reason we are doing these things.

The objectives and measures of success for the final exercise is not clearly articulated, causing me to guess as to what the evaluator had wanted us to do. The instructions said to solve for the four types of methods, but left it to the student as to if they wished to generate graphics, etc. If the only objective was to generate the Jaccard score, F1 score, and LogLoss (as appropriate) to complete the activities, then it should have been stated. In addition, the examples presented in the course labs did not have us generating the F1 and Jaccard scores for many of the models.

創建者 Alexander W

May 07, 2020

Even for an introductory course most lessons lacked depth. Usually the broad idea of an algorithm is introduced and then an exercise shows a python call to which applies it. However neither are there any theoretical/mathematical insights why the algorithm works, nor does one obtain relevant practical knowledge. E.g. the course fails to even superficially explain the many options and parameters each algorithm has and which are necessary to actually apply it in practice.

What makes it worse is that there is apparently no support and maintenance for this course: There are tons of smaller and some larger mistakes in the lectures as well as the exercises, however reports of those as well as most other questions in the discussion forums remain unanswered.

創建者 Reha P

Jul 19, 2020

This course was definitely informative, but the final assignment grading process was ridiculous. There was way too much ambiguity with the grading criteria. I submitted the same exact assignment twice, the first time I got a 13.5 and the second time I got a 25. This should not be possible. Much like some of the other courses in the IBM Data Science certificate program, I HIGHLY suggest adding an image of what the solution should be instead of leaving it up to people to determine what they think is right or wrong. This turned into an all day process for me and I'm beyond frustrated with the course and relieved I'm done with it.

創建者 Ankit K

Jul 27, 2020

Very deep with less, almost zero explanations. Not at all for beginners. Either, it has been given as an overview or should completely moved to Professional Segment.

As I remember, at the very first starting of this IBM course series, it was quoted that you need not to know much coding, but what I am observing by end of the modules, it requires lots of coding.

There must be specific guidelines what to learn, what to master before attempting, otherwise it just becomes a mere certificate.

創建者 Erik D L

Dec 28, 2019

The videos are good, very clear

The lab exercises when compared to rest of the course is not satisfactory because in lab sessions, the algorithms were not explained and lacks Student excercise. It also lacks clarity around when to use which algorithm

almost every lab uses a distinct code compared to other courses i think it needs more commenting i didn' like the final grade either because is very subjective

創建者 Adam S C

Jun 10, 2019

This course has good aims and covers a lot of ground though explanations given for the materials are often confusing over overly complex for the target audience. There are also spelling errors and formatting errors within some of the course contents, which causes issues - particularly for the final assignment. You'll learn a lot on this course but it's definitely not for beginners.

創建者 Vyacheslav I

Dec 09, 2019

It could have been very good. But again, one more useless course by IBM. Your task is to copy-paste without asking any question why and how. Graded assignment is a joke. Sample result notebook is useless as nothing is explained, proposed models are bad and NOT CORRECT in a first place. Just give your money to IBM and don't ask questions

創建者 Yariv Z

Jun 25, 2020

Very superficial. It teaches at a very high level and doesn't go into details in many cases. There are a lot of open questions and I feel as if I just got a taste. It should be the first course in the certificate as an introduction and then there should be dedicated courses.

創建者 Barry y

Jan 16, 2020

Some codes were added but no explanation even. They were fairly complicated and should be elaborated on.

Instructions were also unclear, sometimes we have no idea what the assignment wants. I find my self googling the concepts instead of trying to learn it in this course.

創建者 Vadim S

Apr 18, 2020

Good presentation videos is a plus.

However, the total lack of teachers/mentors support, crowd comments instead of properly designed final project is a much bigger minus.

Don't recommend to anyone who really wants to develop skills, not get a useless paper certificate.

創建者 Christos T

Mar 15, 2020

There are not enough exercises on the application of Machine Learning in Python. Also the server containing the exercises is always down. A lot of type-o mistakes.

The only good thing was the final exercise which was really interesting

創建者 shaurya v s b

Sep 03, 2020

It was a bad experience learning with this course and long codes were there and they were hard to understand . Also the instructor failed to understand the maths behind machine learning. I don't like the course.

創建者 Mark O

Jan 19, 2020

The peer-graded assignment is a mess - especially if you try resubmitting work. There is no incentive or way for peers to grade assignments after they have done their two reviews. Please work on this IBM.

創建者 Michael S

Jul 12, 2019

course was fine, but the review process was bad organized. following the instructions, the reviewer couldn't see the work of the student. also not ideal, that students score the work of other students...

創建者 Jim C

Jul 15, 2019

This course is not as well put together as some of the other Python/Data science courses I've completed. In particular, the final assignment is not clear, as you can tell from viewing the week 6 forum.

創建者 Aravindan N

Aug 13, 2019

Mathematical basis of the algorithms were explained with less emphasis on coding. The coding part along with the algorithms were also not explained in the lab sessions.Needs improvement.

創建者 Chirag G

Aug 06, 2019

Too basic. Also, its easy to pass this course without much efforts. Should include more assignments that require writing bunch of code. Also, should have different project for people.