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Support Vector Machines with scikit-learn(으)로 돌아가기

Coursera Project Network의 Support Vector Machines with scikit-learn 학습자 리뷰 및 피드백

303개의 평가
51개의 리뷰

강좌 소개

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....

최상위 리뷰


2020년 4월 22일

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.


2020년 5월 12일

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

필터링 기준:

Support Vector Machines with scikit-learn의 51개 리뷰 중 1~25

교육 기관: Tanish M S

2020년 3월 30일

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

교육 기관: Rachana C

2020년 3월 28일

Need more thorpugh explanation of python libraries and functions.

교육 기관: Bidyasagar

2020년 9월 6일

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.

교육 기관: Sarthak P

2020년 6월 10일

It Okay types experience.

교육 기관: Satyendra k

2020년 5월 29일

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.

교육 기관: Shubham Y

2020년 5월 13일

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

Will definitely worth your time.

교육 기관: Mayank S

2020년 4월 23일

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.

교육 기관: ANURAG P

2020년 7월 10일

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

교육 기관: Lasal J

2020년 12월 23일

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

교육 기관: Abhishek P G

2020년 6월 18일

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

교육 기관: RUDRA P D

2020년 9월 16일

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

교육 기관: Sebastian J

2020년 4월 15일

Highly recommended to those who have an understanding of SVMs.

교육 기관: Ujjwal K

2020년 5월 9일

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


2020년 5월 8일

I am learning so new things from the topic

교육 기관: Ashwini M

2020년 6월 13일

Very good project .. learned a lot

교육 기관: Arnab S

2020년 10월 12일

Nicely thaught concepts

교육 기관: Shantanu b

2020년 5월 23일

intersting and helpfull

교육 기관: javed a

2020년 6월 25일

Good for the beginners

교육 기관: JONNALA S R

2020년 5월 5일

Good Course

교육 기관: SHIV P S P

2020년 6월 27일



2020년 5월 31일


교육 기관: Kamlesh C

2020년 6월 26일



2020년 6월 26일


교육 기관: p s

2020년 6월 22일


교육 기관: tale p

2020년 6월 18일