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学生对 Coursera Project Network 提供的 Support Vector Machines with scikit-learn 的评价和反馈

122 个评分
25 条评论


In this project, you will learn the functioning and intuition behind a powerful class of supervised linear models known as support vector machines (SVMs). By the end of this project, you will be able to apply SVMs using scikit-learn and Python to your own classification tasks, including building a simple facial recognition model. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

1 - Support Vector Machines with scikit-learn 的 25 个评论(共 27 个)

创建者 Tanish M S

Mar 30, 2020

The instructor has mastery over these topics. I really enjoyed the session!

创建者 Rachana C

Mar 28, 2020

Need more thorpugh explanation of python libraries and functions.

创建者 Satyendra k

May 30, 2020

I am satendra kumar, Ipresuing b. Tech Me lkg ptu main campus kapurthala . I learned about in SVM machine learning, machine learning are three type superwise learning, non superwise learning and re- superwise letaning. SVM likes in the superwise learning. SVM are two types quadrilateral and circle are modle training.

创建者 Shubham Y

May 13, 2020

This guided project will definitely give you a practical approach to what you have read in SVM.

Will definitely worth your time.

创建者 Mayank S

Apr 23, 2020

Learned about SVM.

Need t revisit the code and get most out of it.

Things were concise and that is the strength of the course.

创建者 Sebastian J

Apr 15, 2020

Highly recommended to those who have an understanding of SVMs.

创建者 Ujjwal K

May 09, 2020

Nice Project! But theory should have explained a little more.


May 08, 2020

I am learning so new things from the topic

创建者 Shantanu b

May 23, 2020

intersting and helpfull


May 05, 2020

Good Course


May 31, 2020


创建者 Ankit G

May 28, 2020


创建者 Avik C

May 07, 2020



Jun 01, 2020



May 26, 2020


创建者 Pavan K

May 16, 2020

Beginner friendly and walks you through most of major steps which are usually done in Machine Learning Projects with SVM. Good course

创建者 Devavrat S B

May 09, 2020

It would have been better if the theory would have been explain in more depth.


May 22, 2020

Can improve on explaining theory in detail

创建者 Rohit K

May 28, 2020

Great Content

创建者 Veeramanickam M

May 06, 2020

Good one

创建者 Kiran U K

Apr 18, 2020

content was good, but interface was not user friendly.

Need not provide cloud instance of notebook or could have been in different tab. everything in one tab with no option for user to switch to full screen makes it difficult.

Though the approach of practical coding is appreciated.

创建者 Sahukari o c

May 22, 2020

The course is very understanding, but some modules shown in the course are no longer in the present version so if possible update the videos or mentions the version which is used.

创建者 saihemanth m

May 14, 2020

Explanation of code is not upto mark, and should be explained in more detailed way

创建者 Gadde S S

May 20, 2020

Explanation about the libraries was not enough!

创建者 Tanzim M

Apr 13, 2020

You have made the course too much compact