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Avis et commentaires pour d'étudiants pour Medical Diagnosis using Support Vector Machines par Coursera Project Network

57 évaluations
14 avis

À propos du cours

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 - 14 sur 14 Avis pour Medical Diagnosis using Support Vector Machines

par Vishnu R

11 juil. 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.

par Yasir A

13 sept. 2020

Nice course.

par Nikita H

22 sept. 2020

Good course


11 juil. 2020

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

par Diana C

22 nov. 2020

Just the right amount of explanation and content.


16 sept. 2021

good and useful

par Gregory G J

7 janv. 2021

Thumbs Up!

par Kamlesh C

27 août 2020

Thank you


20 juil. 2020


par Isaac S

8 juil. 2020


par Edward N

25 sept. 2021


par Ran B R

9 juin 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

par Rushikesh S

12 juil. 2020

Good course for practicing SVM Classifiers

par Shubhra P

23 juil. 2020

A very simple example