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Predict Employee Turnover with scikit-learn(으)로 돌아가기

Coursera Project Network의 Predict Employee Turnover with scikit-learn 학습자 리뷰 및 피드백

4.4
별점
242개의 평가
41개의 리뷰

강좌 소개

Welcome to this project-based course on Predicting Employee Turnover with Decision Trees and Random Forests using scikit-learn. In this project, you will use Python and scikit-learn to grow decision trees and random forests, and apply them to an important business problem. Additionally, you will learn to interpret decision trees and random forest models using feature importance plots. Leverage Jupyter widgets to build interactive controls, you can change the parameters of the models on the fly with graphical controls, and see the results in real time! 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 Python, Jupyter, and scikit-learn pre-installed....

최상위 리뷰

RS
2020년 5월 31일

I am glad to have taken this course. I came across some unknown features of Pandas (profile), sklearn library. New python libraries like yellowbrick.

LY
2020년 5월 4일

I was looking for Elaborated explanation of the project and implement it to clear the concept.\n\nThis course did explain it all.

필터링 기준:

Predict Employee Turnover with scikit-learn의 41개 리뷰 중 1~25

교육 기관: UNMILON P

2020년 4월 9일

compact course

교육 기관: Lokesh Y

2020년 5월 5일

I was looking for Elaborated explanation of the project and implement it to clear the concept.

This course did explain it all.

교육 기관: Arnab S

2020년 9월 26일

A good place to learn the implementation of Random Forest and Decision Trees and how to interpret the results.

교육 기관: Taesun Y

2020년 6월 3일

the course was designed well and easy to follow. I was hoping to learn a bit more advanced stuff but picked up some useful libraries that I never used it before. Just watch out for little typo when you named a dataset as "data" and next section of the video you called it "hr". The other thing I noticed that if you re-record the videos without you making mistakes along the way would have been much better for students to follow you and save time. cheers,

교육 기관: Frank M N

2020년 9월 7일

Really liked it! Up to the point on a useful subject which directly translate into business reality. Within that package you get a very nice and detailed forest of random forest!

교육 기관: Alina I H

2020년 11월 9일

Just the perfect course - a well instructed project that helped me exactly with my employee turnover prediction project at work. Thanks from Germany!

교육 기관: Rahul S

2020년 6월 1일

I am glad to have taken this course. I came across some unknown features of Pandas (profile), sklearn library. New python libraries like yellowbrick.

교육 기관: samuel c j

2020년 7월 4일

I learn a lot in a small amount of time. I would like to see more advanced projects from you!

교육 기관: Sebastian J

2020년 4월 28일

Excellent course for those who knowledge on the topics mentioned in the content.

교육 기관: Ricardo D

2020년 9월 29일

Great course. It goes to the point about decision trees and random forests.

교육 기관: Kaushal P

2020년 6월 9일

very useful project, really enjoyed while doing!

교육 기관: Harshit C

2020년 5월 26일

Just right for the basics of Machine Learning

교육 기관: Mayank S

2020년 5월 2일

Good Course. Learned a lot. Thanks Sir.

교육 기관: Ketaki K

2020년 4월 21일

The Course was very productive .

교육 기관: Dr. V Y

2020년 4월 21일

Overall Good Experience

교육 기관: XAVIER S M

2020년 6월 2일

Very Helpful !

교육 기관: Akash

2020년 5월 23일

great learning

교육 기관: Dr. A S A A

2020년 5월 6일

لا يوجد تعليق

교육 기관: Widhi A P

2020년 7월 8일

Very Good

교육 기관: Doss D

2020년 6월 14일

Thank you

교육 기관: Kamlesh C

2020년 7월 6일

THanks

교육 기관: Vajinepalli s s

2020년 6월 18일

nice

교육 기관: tale p

2020년 6월 13일

good

교육 기관: SHIV P S P

2020년 6월 2일

good

교육 기관: abdul r s n

2020년 5월 19일

Best