Chevron Left
返回到 使用 Python 进行机器学习

学生对 IBM 提供的 使用 Python 进行机器学习 的评价和反馈

4.7
9,301 个评分
1,497 条评论

课程概述

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....

热门审阅

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.

RN

May 26, 2020

Labs were incredibly useful as a practical learning tool which therefore helped in the final assignment! I wouldn't have done well in the final assignment without it together with the lecture videos!

筛选依据:

1401 - 使用 Python 进行机器学习 的 1425 个评论(共 1,486 个)

创建者 shankar p

May 28, 2020

Watson Studio was not enough explained. extremely difficult to work on it.

创建者 Jayesh M

Jan 27, 2020

Too complex course, some one will do not understand many things out of it.

创建者 Abdulwahab A

Apr 03, 2020

Was not easy to use the code on my local machine.

I was using spyder IDE

创建者 Vinayak R S

Jul 25, 2019

Should be an extensive course.The coding part should be explained more.

创建者 Madhurima M

May 20, 2020

Lab works are not well explained. Otherwise, it's a great course.

创建者 Chen Y

Mar 27, 2019

The lectures that are longer than 5 minutes are hard to tolerate.

创建者 Rangappa N

Feb 28, 2019

Programming works need to be added,Quiz need to graded for free

创建者 abd-elrhman m

Jul 05, 2020

everything was out of scope it was just a brief of every thing

创建者 Aravind P

Jun 12, 2020

Theory part was awesome. But not much of practical knowledge

创建者 Stefan A

Jun 06, 2020

Lab is working bad so a lot of time is waisted with waiting.

创建者 Ramsrinivas A

Jan 17, 2020

Theoretical portion was shallow compared to Lab portion

创建者 Hunter W I

Apr 21, 2020

Learned a little bit, want more real world application

创建者 SHAONI C

Dec 02, 2019

needs more clarification on classification algorithm

创建者 lorenzo a

Feb 12, 2020

soooo many typoes and small mistakes in this course

创建者 H A H

May 19, 2020

this is good course about basic machine learning..

创建者 Haykel S

Dec 26, 2019

The Correction of assignment is not very correct.

创建者 Abdul R

Mar 28, 2020

Labs Are not responding it sucks a lot

创建者 dk

Nov 23, 2019

不建议新人学,这个是系列课程的一部分,内容不多 只讲个大概给你听

创建者 Omkar A

Jun 17, 2019

Practical Classes were Missing.

创建者 Manoj P

Oct 30, 2018

can be done much better

创建者 Rao M H

Apr 01, 2020

Lab are working worst

创建者 Rajesh K R

Dec 12, 2019

Good for beginners

创建者 Сокол С А

Dec 02, 2019

Too superficial

创建者 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.