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Support Vector Machines with scikit-learn に戻る

Coursera Project Network による Support Vector Machines with scikit-learn の受講者のレビューおよびフィードバック

4.3
301件の評価
51件のレビュー

コースについて

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....

人気のレビュー

MS
2020年4月22日

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
2020年5月12日

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

フィルター:

Support Vector Machines with scikit-learn: 1 - 25 / 51 レビュー

by Tanish M S

2020年3月30日

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

by Rachana C

2020年3月28日

Need more thorpugh explanation of python libraries and functions.

by K B P

2020年9月6日

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.

by Sarthak P

2020年6月10日

It Okay types experience.

by Satyendra k

2020年5月29日

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.

by Shubham Y

2020年5月13日

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

Will definitely worth your time.

by Mayank S

2020年4月23日

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.

by ANURAG P

2020年7月10日

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

by Lasal J

2020年12月23日

Nicely Done, Just wished if we used real-world datasets instead of the sci-kit learn one.

by Abhishek P G

2020年6月18日

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

by RUDRA P D

2020年9月16日

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

by Sebastian J

2020年4月15日

Highly recommended to those who have an understanding of SVMs.

by Ujjwal K

2020年5月9日

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

by SHOMNATH D

2020年5月8日

I am learning so new things from the topic

by Ashwini M

2020年6月13日

Very good project .. learned a lot

by Arnab S

2020年10月12日

Nicely thaught concepts

by Shantanu b

2020年5月23日

intersting and helpfull

by javed a

2020年6月25日

Good for the beginners

by JONNALA S R

2020年5月5日

Good Course

by SHIV P S P

2020年6月27日

aewsome

by SUDARSHINI A

2020年5月31日

Nothing

by Kamlesh C

2020年6月26日

thanks

by KARUNANIDHI D

2020年6月26日

Good

by p s

2020年6月22日

Nice

by tale p

2020年6月18日

good