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学生对 Coursera Project Network 提供的 Medical Diagnosis using Support Vector Machines 的评价和反馈

4.5
57 个评分
14 条评论

课程概述

In this one hour long project-based course, you will learn the basics of support vector machines using Python and scikit-learn. The dataset we are going to use comes from the National Institute of Diabetes and Digestive and Kidney Diseases, and contains anonymized diagnostic measurements for a set of female patients. We will train a support vector machine to predict whether a new patient has diabetes based on such measurements. By the end of this course, you will be able to model an existing dataset with the goal of making predictions about new data. This is a first step on the path to mastering machine learning. Note: 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....

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1 - Medical Diagnosis using Support Vector Machines 的 14 个评论(共 14 个)

创建者 Vishnu R

Jul 11, 2020

This is not a real world data. Instructor is showing a very basic example. I guess he could have done a real world problem which is little challenging and useful to participants.

创建者 Yasir A

Sep 13, 2020

Nice course.

创建者 Nikita H

Sep 22, 2020

Good course

创建者 ANURAG P

Jul 11, 2020

A short duration course but with deep and effective learnings. This will give you some insights regarding the power of SVMs

创建者 Diana C

Nov 22, 2020

Just the right amount of explanation and content.

创建者 ESTEBAN P J

Sep 16, 2021

good and useful

创建者 Gregory G J

Jan 7, 2021

Thumbs Up!

创建者 Kamlesh C

Aug 27, 2020

Thank you

创建者 VINAYAK M

Jul 20, 2020

Excellent

创建者 Isaac S

Jul 8, 2020

Thanks

创建者 Edward N

Sep 25, 2021

a1

创建者 Ran B R

Jun 9, 2021

Quick and basic intro to SVM training. Clearly explained each step and pointed out some issues to avoid. I'd have liked a little explanation of *how* SVMs work (even just how predictions are made once model is trained), but it being "beyond the scope of the project" is not unreasonable

创建者 Rushikesh S

Jul 12, 2020

Good course for practicing SVM Classifiers

创建者 Shubhra P

Jul 23, 2020

A very simple example