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Support Vector Machines in Python, From Start to Finish(으)로 돌아가기

Coursera Project Network의 Support Vector Machines in Python, From Start to Finish 학습자 리뷰 및 피드백

4.6
별점
142개의 평가
22개의 리뷰

강좌 소개

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....

최상위 리뷰

AH
2020년 4월 15일

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
2020년 6월 8일

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

필터링 기준:

Support Vector Machines in Python, From Start to Finish의 22개 리뷰 중 1~22

교육 기관: ilay

2020년 6월 6일

the remote desktop is impossible to work with.

just let me work on the jupyter lab...

very low level of course

교육 기관: Anuganti S

2020년 6월 5일

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.

교육 기관: Muhammet N C

2020년 9월 17일

Short and understandable. Plus, Josh Starmer is a great instructor.

교육 기관: Ali M H

2020년 4월 16일

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.

교육 기관: Mofei W

2020년 11월 4일

Best instructor I've ever had. I'm a huge fan of all of your stats videos! Awesome awesome work and I'm really looking forward to more in ML!!!

교육 기관: Gouri S

2020년 6월 9일

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

Thank You sir.

교육 기관: Mayank S

2020년 4월 30일

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

교육 기관: vivek d

2020년 7월 21일

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

교육 기관: Rushikesh S

2020년 8월 7일

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

교육 기관: Vedang B

2020년 10월 18일

Short concise and precise course for learning SVM.

교육 기관: Yasir A

2020년 9월 11일

Very helpful. Great instructor.

교육 기관: Abhimanyu D

2020년 5월 9일

nice course

교육 기관: Doss D

2020년 6월 19일

Thank you

교육 기관: Uppalapati. S S

2020년 6월 20일

Great

교육 기관: Manish N

2021년 5월 2일

Good

교육 기관: p s

2020년 6월 25일

Good

교육 기관: tale p

2020년 6월 23일

good

교육 기관: FRANSESCO M

2020년 6월 22일

Best

교육 기관: Vajinepalli s s

2020년 6월 16일

nice

교육 기관: BHARATH M

2020년 6월 7일

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.

교육 기관: Nilesh A

2020년 5월 17일

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.

교육 기관: Nikhil T

2020년 7월 8일

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