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Coursera Project Network による Predict Employee Turnover with scikit-learn の受講者のレビューおよびフィードバック

4.4
165件の評価
31件のレビュー

コースについて

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....

人気のレビュー

RS

Jun 01, 2020

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

May 05, 2020

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

フィルター:

Predict Employee Turnover with scikit-learn: 1 - 25 / 32 レビュー

by UNMILON P

Apr 09, 2020

compact course

by Taesun Y

Jun 04, 2020

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,

by Rahul S

Jun 01, 2020

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

by lokesh y

May 05, 2020

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

This course did explain it all.

by samuel c j

Jul 05, 2020

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

by Sebastian J

Apr 28, 2020

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

by Kaushal P

Jun 09, 2020

very useful project, really enjoyed while doing!

by Harshit C

May 26, 2020

Just right for the basics of Machine Learning

by Mayank S

May 02, 2020

Good Course. Learned a lot. Thanks Sir.

by Ketaki K

Apr 21, 2020

The Course was very productive .

by Dr. V Y

Apr 21, 2020

Overall Good Experience

by XAVIER S M

Jun 02, 2020

Very Helpful !

by Akash

May 23, 2020

great learning

by Dr. A S A A

May 06, 2020

لا يوجد تعليق

by Doss D

Jun 14, 2020

Thank you

by Vajinepalli s s

Jun 18, 2020

nice

by tale p

Jun 13, 2020

good

by SHIV P S P

Jun 02, 2020

good

by abdul r s n

May 19, 2020

Best

by Karan G

Jun 08, 2020

Most of the things that were used were not discussed on how to install them. This consumes a lot of time searching them over the internet.

Also, some of the python libraries that were used are deprecated and are not running on our notebooks. This is also not discussed in great detail

by Murtuza B

Jun 28, 2020

Get to learn something new. Like I have not used the interactive dashboard when creating the model. Also get to know about some very useful libraries that I was not using before and I used them more often. Thank you so much for your time and efforts creating this.

by Samridha K

May 07, 2020

Very good content and specific. Very satisfied. However my only complaint is that I hope the creator had explained the interactive decision tree and rf codes such as setting gini, entropy and other min, max values more with reasoning.

by aathira s

Jun 12, 2020

Doing hands on project on Rhyme was very helpful as we could listen to the instructions and learn and type it ourselves.

by Frank J C I

Jun 14, 2020

Interesting project! It could be better if the course explores more theorical fundamentals of the algorithms

by Erwin D

May 13, 2020

Excellent approach to predicting employee turnovers!