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Вернуться к Multiple Linear Regression with scikit-learn

Отзывы учащихся о курсе Multiple Linear Regression with scikit-learn от партнера Coursera Project Network

Оценки: 340

О курсе

In this 2-hour long project-based course, you will build and evaluate multiple linear regression models using Python. You will use scikit-learn to calculate the regression, while using pandas for data management and seaborn for data visualization. The data for this project consists of the very popular Advertising dataset to predict sales revenue based on advertising spending through media such as TV, radio, and newspaper. By the end of this project, you will be able to: - Build univariate and multivariate linear regression models using scikit-learn - Perform Exploratory Data Analysis (EDA) and data visualization with seaborn - Evaluate model fit and accuracy using numerical measures such as R² and RMSE - Model interaction effects in regression using basic feature engineering techniques 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, this means instant access to a cloud desktop with Jupyter Notebooks and Python 3.7 with all the necessary libraries pre-installed. 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....

Лучшие рецензии


15 сент. 2020 г.

This project is great. Clearly explained and well delivered. I will highly recommend to take this project. The instructor is great!


7 февр. 2021 г.

Well paced, very informative, I felt I learnt skills that I can apply to practical problems immediately.

Фильтр по:

26–50 из 54 отзывов о курсе Multiple Linear Regression with scikit-learn


16 сент. 2020 г.


автор: tale p

26 июня 2020 г.


автор: p s

25 июня 2020 г.


автор: Vajinepalli s s

16 июня 2020 г.


автор: Abhishek P G

15 июня 2020 г.


автор: Katamreddy M r

27 июня 2020 г.


автор: YOGESH P

1 июля 2020 г.

The course is well structured and all the important theories and concepts have been explained in a quite detailed fashion. One should definitely try out this course to strengthen their skills in foundational level machine learning.

автор: Nikhil T

6 июля 2020 г.

This course who wants to learn about basics and he has made it understand quite fine and apart from it quiz is very easy so you will pass but i would request him to atleast have 2 or more examples it would be much more better

автор: Shubham A

15 апр. 2020 г.

Great course. Thanks to the instructor, The rhyme platform is sometimes very slow, content: (7/10),Audio clarity: (5/10), video clarity: (8/10), Rhyme platform performance: (4/10).

автор: NHM H I C

17 апр. 2020 г.

Very good for freshers. Discussed the basic concepts and implemented them. They have a virtual computer so you need not install or download anything.

автор: Isah A

24 нояб. 2020 г.

Nice project for beginners. In the last video, there was a very useful concept of synergy which could be helpful for intermediate learners.

автор: Pavithra K

24 авг. 2020 г.

good for beginners, loved the way the instructor explained about synergy (interaction among features)

автор: Pratham A

11 июня 2020 г.

Overall a good project, just a few functions here and there whose use I needed to figure out myself.

автор: Hariprasad M

26 июня 2020 г.

The project explained the basic concepts effectively but it is very short. Otherwise, it's good.

автор: Sanketh R P

16 мая 2020 г.

Whatever explained is satisfactory ,but it is short.We looking for more big projects.

автор: Ammar S

6 июля 2020 г.

Good analyzing ideas and efficient visualization metrics.

автор: Yash S

28 июня 2020 г.

there was no sound in video no. 6 after minute

автор: Rohit k

1 июня 2020 г.

It is very is easy to understand .

автор: Chintoo K

11 сент. 2020 г.


автор: SHRUTI S

14 мая 2020 г.

Best for beginners

автор: Alan B

16 апр. 2020 г.

Good course

автор: K S

16 июня 2020 г.

just right

автор: chaitanya d

9 мая 2020 г.

very good

автор: M M A

23 июля 2020 г.


автор: ANIL V

2 мая 2020 г.

The initiative by coursera is good. But the instructor made so many mistakes and typos, seems like he is not serious about his work.