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.
RK
It was clear to understand any student to learn linear regression with python
AR
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
CB
Great project best for people who wants to better understand the maths behind machine learning
RS
The guided project is nice for the beginners. The only problem I had was to figure out what is the right learning rate for the solution. and I am still not able to figure it out.
AP
Great to perform hands-on training while learning through the video lecture
MS
Very practical class. Just with less than an hour I got good idea. Thank Coursera and the instructor
DW
This topic is useful for Algebraic Linear Regression Equation.
PP
Great course.Learn new topics like forward passing and backward passing to update parameters for prediction in regression
KN
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
V
linear Regression with python is very full for project implementation as well as Research data implementation.
GV
good course and taught new concepts of libraries in python
AS
Good refresher course on linear regression! It would have been great had the Instructor covered few of the statical tests or multivariate regression model.
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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
Great to perform hands-on training while learning through the video lecture
Good with the whole explanation from scratch
Good Fundamentals of Linear Regression
The course instructor is amazing.
Good Experience
Great Course
Nice course
Awesome
good
Good
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
It was clear to understand any student to learn linear regression with python
Good for beginners, interface could have been better
good ,it helps to students for learning
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.
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 :)
The project is well-structured and practical. It introduces the fundamentals of linear regression and its implementation using Python in a very intuitive way. The hands-on projects provide valuable real-world experience, and the instructor's clear explanations make complex concepts accessible.
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.
Good refresher course on linear regression! It would have been great had the Instructor covered few of the statical tests or multivariate regression model.