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Kursteilnehmer-Bewertung und -Feedback für Support Vector Machines with scikit-learn von Coursera Project Network

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239 Bewertungen
42 Bewertungen

Über den Kurs

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....

Top-Bewertungen

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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1 - 25 von 42 Bewertungen für Support Vector Machines with scikit-learn

von Tanish M S

Mar 30, 2020

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

von Rachana C

Mar 28, 2020

Need more thorpugh explanation of python libraries and functions.

von 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.

von 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.

von 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.

von Abhishek P G

Jun 18, 2020

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

von Sebastian J

Apr 15, 2020

Highly recommended to those who have an understanding of SVMs.

von Ujjwal K

May 09, 2020

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

von SHOMNATH D

May 08, 2020

I am learning so new things from the topic

von ASHWINI K M

Jun 13, 2020

Very good project .. learned a lot

von Shantanu b

May 23, 2020

intersting and helpfull

von javed a

Jun 25, 2020

Good for the beginners

von JONNALA S R

May 05, 2020

Good Course

von SHIV P S P

Jun 27, 2020

aewsome

von SUDARSHINI A

May 31, 2020

Nothing

von Kamlesh C

Jun 27, 2020

thanks

von KARUNANIDHI D

Jun 26, 2020

Good

von p s

Jun 22, 2020

Nice

von tale p

Jun 18, 2020

good

von Vajinepalli s s

Jun 17, 2020

nice

von Ankit G

May 28, 2020

nice

von Avik C

May 07, 2020

Good

von PONDARA K

Jun 01, 2020

5

von MANIKANTA S

May 26, 2020

5

von 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.