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Вернуться к Predict Employee Turnover with scikit-learn

Отзывы учащихся о курсе Predict Employee Turnover with scikit-learn от партнера Coursera Project Network

4.4
звезд
Оценки: 242
Рецензии: 41

О курсе

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....

Лучшие рецензии

RS
31 мая 2020 г.

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 мая 2020 г.

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

Фильтр по:

1–25 из 41 отзывов о курсе Predict Employee Turnover with scikit-learn

автор: UNMILON P

9 апр. 2020 г.

compact course

автор: Lokesh Y

5 мая 2020 г.

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

This course did explain it all.

автор: Arnab S

26 сент. 2020 г.

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

автор: Taesun Y

3 июня 2020 г.

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,

автор: Frank M N

7 сент. 2020 г.

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!

автор: Alina I H

9 нояб. 2020 г.

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

автор: Rahul S

1 июня 2020 г.

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

автор: samuel c j

4 июля 2020 г.

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

автор: Sebastian J

28 апр. 2020 г.

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

автор: Ricardo D

29 сент. 2020 г.

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

автор: Kaushal P

9 июня 2020 г.

very useful project, really enjoyed while doing!

автор: Harshit C

26 мая 2020 г.

Just right for the basics of Machine Learning

автор: Mayank S

2 мая 2020 г.

Good Course. Learned a lot. Thanks Sir.

автор: Ketaki K

21 апр. 2020 г.

The Course was very productive .

автор: Dr. V Y

21 апр. 2020 г.

Overall Good Experience

автор: XAVIER S M

2 июня 2020 г.

Very Helpful !

автор: Akash

23 мая 2020 г.

great learning

автор: Dr. A S A A

6 мая 2020 г.

لا يوجد تعليق

автор: Widhi A P

8 июля 2020 г.

Very Good

автор: Doss D

14 июня 2020 г.

Thank you

автор: Kamlesh C

6 июля 2020 г.

THanks

автор: Vajinepalli s s

18 июня 2020 г.

nice

автор: tale p

13 июня 2020 г.

good

автор: SHIV P S P

2 июня 2020 г.

good

автор: abdul r s n

19 мая 2020 г.

Best