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返回到 Support Vector Machines in Python, From Start to Finish

学生对 Coursera Project Network 提供的 Support Vector Machines in Python, From Start to Finish 的评价和反馈

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96 个评分
17 条评论

课程概述

In this lesson we will built this Support Vector Machine for classification using scikit-learn and the Radial Basis Function (RBF) Kernel. Our training data set contains continuous and categorical data from the UCI Machine Learning Repository to predict whether or not a patient has heart disease. 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 (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with programming in Python and the concepts behind Support Vector Machines, the Radial Basis Function, Regularization, Cross Validation and Confusion Matrices. 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....

热门审阅

AH

Apr 16, 2020

It was amazing lecture and teach special with SVM in Python I did learn a lot from him via his tasked. I will download his videos all each tasked have a part of explanation.

GS

Jun 09, 2020

This is a very good course to start with SVM.I now know the basic coding for SVM.\n\nThank You sir.

筛选依据:

1 - Support Vector Machines in Python, From Start to Finish 的 17 个评论(共 17 个)

创建者 Anuganti S

Jun 05, 2020

Nice explanation. Each and every step explained well and in notebook written good explanation.

Thanks for the Project explanation, practice and skill test.

skill test questions is very useful and to gain knowledge on SVM.

创建者 Ali M H

Apr 16, 2020

It was amazing lecture and teach special with SVM in Python I did learn a lot from him via his tasked. I will download his videos all each tasked have a part of explanation.

创建者 Gouri S

Jun 09, 2020

This is a very good course to start with SVM.I now know the basic coding for SVM.

Thank You sir.

创建者 Mayank S

Apr 30, 2020

Great Course. Designed nicely, easy to understand. Now i know how to use SVM.

创建者 vivek d

Jul 21, 2020

I am a beginner in this area but I learned a lot in this course.

创建者 Rushikesh S

Aug 07, 2020

Excellent Teaching. Makes it easier for you to understand SVM.

创建者 Abhimanyu

May 09, 2020

nice course

创建者 Doss D

Jun 19, 2020

Thank you

创建者 Uppalapati. S S

Jun 21, 2020

Great

创建者 p s

Jun 25, 2020

Good

创建者 tale p

Jun 23, 2020

good

创建者 FRANSESCO M

Jun 22, 2020

Best

创建者 Vajinepalli s s

Jun 16, 2020

nice

创建者 BHARATH M

Jun 07, 2020

Although there are many lectures on SVM, I have opted for this because of the name " Josh Starmer" BAMM..!! I am a great follower of his youtube videos and I like the way he explains things in easy and understandable way. I hope I have learnt many things to mess around with Support vector Machines. This even helps me in my class project.

创建者 Nilesh A

May 17, 2020

The course really picks up nice on reading, formatting, handling missing values but it's stretched too much and the re-reading of the jupyter notebook seemed too much for me. In the end, I do understand only a bit of SVM's implementation and optimization but not really the concept of SVM.

创建者 Nikhil T

Jul 08, 2020

Initially it was explained but after some point he just started reading the code

创建者 ilay

Jun 06, 2020

the remote desktop is impossible to work with.

just let me work on the jupyter lab...

very low level of course