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學生對 Coursera Project Network 提供的 Support Vector Machines with scikit-learn 的評價和反饋

4.3
267 個評分
44 條評論

課程概述

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....

熱門審閱

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.

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26 - Support Vector Machines with scikit-learn 的 44 個評論(共 44 個)

創建者 Yogesh P

Jul 23, 2020

The theoretical concepts related to Support Vector Machines are explained to a fair extent. Although, I would advise you to gather a good knowledge on this topic to get the most out of this course. The instructor really guides you throughout the course of the project. However, you might sometimes feel like you're missing out on some aspects of the topic but hang on, and you'll be good to go by the end of this project.

創建者 Shobhit U

Jun 05, 2020

It is a good project but you need familiar background of all the libraries and a bit of knowledge from your part on support vector machines, which I think is okay, because guided projects can only understood if you have the basics with you.

創建者 B A

Jun 26, 2020

It might be difficult for some people to understand this course who have zero knowledge of machine learning. Overall the course was good.

創建者 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

創建者 Devavrat S B

May 09, 2020

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

創建者 Gurucharan C

May 22, 2020

Can improve on explaining theory in detail

創建者 Md. M H

Jun 03, 2020

effective course for beginner

創建者 Rohit K

May 28, 2020

Great Content

創建者 Suraj

Jun 04, 2020

thank you!

創建者 Veeramanickam M

May 06, 2020

Good one

創建者 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.

創建者 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.

創建者 saihemanth m

May 14, 2020

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

創建者 Gadde S S

May 20, 2020

Explanation about the libraries was not enough!

創建者 Tanzim M

Apr 13, 2020

You have made the course too much compact

創建者 Sarthak P

Jun 10, 2020

It Okay types experience.

創建者 Konthalapalli S C

May 04, 2020

good

創建者 manam r

May 21, 2020

Library functions are not explained in detail and for beginners its difficult to understand them.

創建者 dhruvi

Jun 11, 2020

kernel trick that was mentioned is not talked about