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Opiniones y comentarios de aprendices correspondientes a Predict Employee Turnover with scikit-learn por parte de Coursera Project Network

4.4
estrellas
242 calificaciones
41 reseña

Acerca del Curso

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....

Principales reseñas

RS
31 de may. de 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
4 de may. de 2020

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

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1 - 25 de 41 revisiones para Predict Employee Turnover with scikit-learn

por UNMILON P

9 de abr. de 2020

compact course

por Lokesh Y

5 de may. de 2020

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

This course did explain it all.

por Arnab S

26 de sep. de 2020

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

por Taesun Y

3 de jun. de 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,

por Frank M N

7 de sep. de 2020

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!

por Alina I H

9 de nov. de 2020

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

por Rahul S

1 de jun. de 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.

por samuel c j

4 de jul. de 2020

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

por Sebastian J

28 de abr. de 2020

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

por Ricardo D

29 de sep. de 2020

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

por Kaushal P

9 de jun. de 2020

very useful project, really enjoyed while doing!

por Harshit C

26 de may. de 2020

Just right for the basics of Machine Learning

por Mayank S

2 de may. de 2020

Good Course. Learned a lot. Thanks Sir.

por Ketaki K

21 de abr. de 2020

The Course was very productive .

por Dr. V Y

21 de abr. de 2020

Overall Good Experience

por XAVIER S M

2 de jun. de 2020

Very Helpful !

por Akash

23 de may. de 2020

great learning

por Dr. A S A A

6 de may. de 2020

لا يوجد تعليق

por Widhi A P

8 de jul. de 2020

Very Good

por Doss D

14 de jun. de 2020

Thank you

por Kamlesh C

6 de jul. de 2020

THanks

por Vajinepalli s s

18 de jun. de 2020

nice

por tale p

13 de jun. de 2020

good

por SHIV P S P

2 de jun. de 2020

good

por abdul r s n

19 de may. de 2020

Best