Chevron Left
Вернуться к Linear Regression with Python

Отзывы учащихся о курсе Linear Regression with Python от партнера Coursera Project Network

4.6
звезд
Оценки: 392
Рецензии: 45

О курсе

In this 2-hour long project-based course, you will learn how to implement Linear Regression using Python and Numpy. Linear Regression is an important, fundamental concept if you want break into Machine Learning and Deep Learning. Even though popular machine learning frameworks have implementations of linear regression available, it's still a great idea to learn to implement it on your own to understand the mechanics of optimization algorithm, and the training process. Since this is a practical, project-based course, you will need to have a theoretical understanding of linear regression, and gradient descent. We will focus on the practical aspect of implementing linear regression with gradient descent, but not on the theoretical aspect. Note: 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

AS
4 июня 2020 г.

Good refresher course on linear regression! It would have been great had the Instructor covered few of the statical tests or multivariate regression model.

PP
24 мая 2020 г.

Great course.\n\nLearn new topics like forward passing and backward passing to update parameters for prediction in regression

Фильтр по:

1–25 из 44 отзывов о курсе Linear Regression with Python

автор: Keerthana N

17 апр. 2020 г.

This was my first guided project on coursera and I decided to go with something small. This project just motivated me to take up more projects on the platform

автор: AKASH M P

26 апр. 2020 г.

Great to perform hands-on training while learning through the video lecture

автор: Sarthak M P

29 апр. 2020 г.

Good with the whole explanation from scratch

автор: ABHIRUP H

14 мая 2020 г.

Good Fundamentals of Linear Regression

автор: Muhammad M

20 апр. 2020 г.

The course instructor is amazing.

автор: Radhemohan Y

30 апр. 2020 г.

Good Experience

автор: Ashwin P

21 апр. 2020 г.

Great Course

автор: MARAM A G

13 мая 2020 г.

Nice course

автор: purnachand k

12 мая 2020 г.

Awesome

автор: Rohith

14 мая 2020 г.

good

автор: Aatif J

24 апр. 2020 г.

Good

автор: ADITYA R

3 апр. 2020 г.

Explain more about what the code do, as I've to google it and try to figure out which wasted a lot of time, thank you

автор: Rupali K

18 апр. 2020 г.

It was clear to understand any student to learn linear regression with python

автор: PRASANNA V R

19 апр. 2020 г.

Good for beginners, interface could have been better

автор: SUPRIYA A

16 мая 2020 г.

good ,it helps to students for learning

автор: Ratnadeep M

5 июня 2020 г.

The course was very nice, I have experienced this kind of learning first time where I can do the task along with the instructor which was very exciting. Only the Rhyme platform lags a bit, otherwise everything is perfect. Though some parts could have been explained in detailed manner. But those who have some basic knowledge of Python and higher level mathematics can easily do this course. I will surely recommend it to others.

автор: Carla S S J

28 окт. 2020 г.

I liked the hands-on project a lot, I have followed some courses related to linear regression already and being able to put the theory to practice with this project was really good. Also, I appreciate that the instructor explains with enough detail the steps to be follow and, even as a rookie in python, understanding how to create the model was easy thanks to him :)

автор: Marc L

6 окт. 2020 г.

This was a good course. The VM got a little glitchy a couple of times, but nothing too bad. If you aren't familiar with the mechanics of linear regression and the gradient descent algorithm, take a look before you do the project. That's what I did and it served me very well.

автор: Atul S

5 июня 2020 г.

Good refresher course on linear regression! It would have been great had the Instructor covered few of the statical tests or multivariate regression model.

автор: Parth P

25 мая 2020 г.

Great course.

Learn new topics like forward passing and backward passing to update parameters for prediction in regression

автор: VADTHE N

4 авг. 2020 г.

linear Regression with python is very full for project implementation as well as Research data implementation.

автор: Muruganandan S

31 мая 2020 г.

Very practical class. Just with less than an hour I got good idea. Thank Coursera and the instructor

автор: Dr. P W

28 мая 2020 г.

This topic is useful for Algebraic Linear Regression Equation.

автор: Nilesh S

21 сент. 2020 г.

Easy to follow and just right amount of content.

автор: KATARI L S

11 июля 2020 г.

ONE CAN UNDERSTAND CONCEPTS OF LINEAR REGRESSION