Retour à Medical Diagnosis using Support Vector Machines
Avis et commentaires pour d'étudiants pour Medical Diagnosis using Support Vector Machines par Coursera Project Network
44 évaluations
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 - 10 sur 10 Avis pour Medical Diagnosis using Support Vector Machines
par MD. Y A
•13 sept. 2020
Nice course.
par Nikita H
•22 sept. 2020
Good course
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 ANURAG P
•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.
par Kamlesh C
•27 août 2020
Thank you
par VINAYAK M
•20 juil. 2020
Excellent
par Isaac S
•8 juil. 2020
Thanks
par Rushikesh S
•12 juil. 2020
Good course for practicing SVM Classifiers
par Shubhra P
•23 juil. 2020
A very simple example
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