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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

4.3
289 个评分
48 条评论

课程概述

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....

热门审阅

MS

Apr 23, 2020

Learned about SVM.\n\nNeed t revisit the code and get most out of it.\n\nThings were concise and that is the strength of the course.

SY

May 13, 2020

This guided project will definitely give you a practical approach to what you have read in SVM.\n\nWill definitely worth your time.

筛选依据:

1 - Support Vector Machines with scikit-learn 的 25 个评论(共 48 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 K B S P

Sep 06, 2020

The explanation could have been better. I didn't understand the reason behind giving less importance to the conceptual topics. Hope to see some good explanation from other projects.

创建者 Sarthak P

Jun 10, 2020

It Okay types experience.

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 ANURAG P

Jul 10, 2020

Application-based course with detailed knowledge of SVMs along with an implementation in image classification

创建者 Abhishek P G

Jun 18, 2020

I am grateful to have the chance to participate in an online course like this!

创建者 RUDRA P D

Sep 17, 2020

The course is like a crash course on SVMs with good explanation of concepts.

创建者 Sebastian J

Apr 15, 2020

Highly recommended to those who have an understanding of SVMs.

创建者 Ujjwal K 4 B P E & T I V

May 09, 2020

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

创建者 SHOMNATH D

May 08, 2020

I am learning so new things from the topic

创建者 Ashwini M

Jun 13, 2020

Very good project .. learned a lot

创建者 Arnab S

Oct 12, 2020

Nicely thaught concepts

创建者 Shantanu b

May 23, 2020

intersting and helpfull

创建者 javed a

Jun 25, 2020

Good for the beginners

创建者 JONNALA S R

May 05, 2020

Good Course

创建者 SHIV P S P

Jun 27, 2020

aewsome

创建者 SUDARSHINI A

May 31, 2020

Nothing

创建者 Kamlesh C

Jun 27, 2020

thanks

创建者 KARUNANIDHI D

Jun 26, 2020

Good

创建者 p s

Jun 22, 2020

Nice

创建者 tale p

Jun 18, 2020

good

创建者 Vajinepalli s s

Jun 17, 2020

nice