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Title: Starting With Linear Regression in Python (Overview) (Video) – Real Python

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Description: Hey there. Welcome to this Real Python course on implementing linear regression in Python. What is regression? Regression analysis is a statistical method for estimating the relationship between a dependent variable and one or more independent…

Open Graph Description: Hey there. Welcome to this Real Python course on implementing linear regression in Python. What is regression? Regression analysis is a statistical method for estimating the relationship between a dependent variable and one or more independent…

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00:00https://realpython.com/courses/python-linear-regression/continue/#t=0.48
Hey there.https://realpython.com/courses/python-linear-regression/continue/#t=0.48
Welcome to this Real Python course on implementing linear regression in Python.https://realpython.com/courses/python-linear-regression/continue/#t=1.11
00:07https://realpython.com/courses/python-linear-regression/continue/#t=7.63
What is regression?https://realpython.com/courses/python-linear-regression/continue/#t=7.63
Regression analysis is a statistical method for estimating the relationshiphttps://realpython.com/courses/python-linear-regression/continue/#t=9.43
between a dependent variable and one or more independent variables.https://realpython.com/courses/python-linear-regression/continue/#t=13.69
00:19https://realpython.com/courses/python-linear-regression/continue/#t=19.27
Regression techniques are used in all branches of the sciences and finance.https://realpython.com/courses/python-linear-regression/continue/#t=19.27
The two main uses of regression are prediction and inference. Inhttps://realpython.com/courses/python-linear-regression/continue/#t=24.49
prediction,https://realpython.com/courses/python-linear-regression/continue/#t=29.38
the goal is to forecast the outcome of some event, state, or object from somehttps://realpython.com/courses/python-linear-regression/continue/#t=30.22
previous knowledge. Whereas in inference,https://realpython.com/courses/python-linear-regression/continue/#t=34.87
your goal is to determine whether an event,https://realpython.com/courses/python-linear-regression/continue/#t=37.96
a state, or an object affects the production of another event, state, or object.https://realpython.com/courses/python-linear-regression/continue/#t=40.0
00:45https://realpython.com/courses/python-linear-regression/continue/#t=45.7
When used for prediction,https://realpython.com/courses/python-linear-regression/continue/#t=45.7
regression analysis has substantial overlap with the field of machine learning.https://realpython.com/courses/python-linear-regression/continue/#t=47.11
00:54https://realpython.com/courses/python-linear-regression/continue/#t=54.25
In regression,https://realpython.com/courses/python-linear-regression/continue/#t=54.25
the goal is to build a mathematical model describing the effect of a set ofhttps://realpython.com/courses/python-linear-regression/continue/#t=55.27
input variables on another variable y.https://realpython.com/courses/python-linear-regression/continue/#t=59.53
The input variables are sometimes called predictors,https://realpython.com/courses/python-linear-regression/continue/#t=61.87
independent variables, or features. The variable y is called thehttps://realpython.com/courses/python-linear-regression/continue/#t=67.03
response, the output, or the dependent variable. As an example,https://realpython.com/courses/python-linear-regression/continue/#t=72.01
y might be the sale price of a home,https://realpython.com/courses/python-linear-regression/continue/#t=77.14
and the independent variables might be the square footage of the home,https://realpython.com/courses/python-linear-regression/continue/#t=80.08
the proximity of the home to schools, the proximity of the home to hospitals,https://realpython.com/courses/python-linear-regression/continue/#t=84.28
or maybe the sell price of other homes in the same neighborhood.https://realpython.com/courses/python-linear-regression/continue/#t=89.08
01:33https://realpython.com/courses/python-linear-regression/continue/#t=93.34
In regression,https://realpython.com/courses/python-linear-regression/continue/#t=93.34
you assume some mathematical model between y and x. Here,https://realpython.com/courses/python-linear-regression/continue/#t=94.27
f is the model. It’s a function of x,https://realpython.com/courses/python-linear-regression/continue/#t=99.16
and the response depends on the model plus some random error term (ε).https://realpython.com/courses/python-linear-regression/continue/#t=102.4
01:48https://realpython.com/courses/python-linear-regression/continue/#t=108.25
So the main goal of regression is to build a good model for f.https://realpython.com/courses/python-linear-regression/continue/#t=108.25
01:54https://realpython.com/courses/python-linear-regression/continue/#t=114.16
To build the model, you need data. In other words,https://realpython.com/courses/python-linear-regression/continue/#t=114.16
you need observations or actual measurements.https://realpython.com/courses/python-linear-regression/continue/#t=117.25
So in the example of the sell price of a home,https://realpython.com/courses/python-linear-regression/continue/#t=120.49
you’ve got the data for the sell price of one home, another home,https://realpython.com/courses/python-linear-regression/continue/#t=123.22
a third home, and so on.https://realpython.com/courses/python-linear-regression/continue/#t=128.08
02:11https://realpython.com/courses/python-linear-regression/continue/#t=131.41
The gist of a regression technique—https://realpython.com/courses/python-linear-regression/continue/#t=131.41
so what differentiates it among others—is how you take the n observationshttps://realpython.com/courses/python-linear-regression/continue/#t=133.21
to build the model f. There are many regression techniques:https://realpython.com/courses/python-linear-regression/continue/#t=138.16
linear, polynomial regression, nonlinear regression, decision trees,https://realpython.com/courses/python-linear-regression/continue/#t=142.72
support vector machines, neural networks, and many others.https://realpython.com/courses/python-linear-regression/continue/#t=147.4
02:32https://realpython.com/courses/python-linear-regression/continue/#t=152.5
In this course,https://realpython.com/courses/python-linear-regression/continue/#t=152.5
you’re going to learn how to use the Python module scikit-learn to implementhttps://realpython.com/courses/python-linear-regression/continue/#t=153.43
linear regression and the related polynomial regression.https://realpython.com/courses/python-linear-regression/continue/#t=157.57
Why linear regression? Well,https://realpython.com/courses/python-linear-regression/continue/#t=162.07
linear regression is the most widely used regression method. In linearhttps://realpython.com/courses/python-linear-regression/continue/#t=164.83
regression, the model f is assumed to take the following form.https://realpython.com/courses/python-linear-regression/continue/#t=169.21
02:54https://realpython.com/courses/python-linear-regression/continue/#t=174.19
The input variables appear linearly in the model,https://realpython.com/courses/python-linear-regression/continue/#t=174.19
and you have a constant term (𝑏₀),https://realpython.com/courses/python-linear-regression/continue/#t=177.73
which is sometimes called the bias or the intercept.https://realpython.com/courses/python-linear-regression/continue/#t=179.32
scikit-learn is used in machine learning and built on top of the popular modulehttps://realpython.com/courses/python-linear-regression/continue/#t=183.52
NumPy.https://realpython.com/courses/python-linear-regression/continue/#t=188.11
03:11https://realpython.com/courses/python-linear-regression/continue/#t=191.05
Let’s talk a little bit about the environment that I’ll be using for the course.https://realpython.com/courses/python-linear-regression/continue/#t=191.05
You’re going to need scikit-learn. You can use pip to install it,https://realpython.com/courses/python-linear-regression/continue/#t=195.13
or if you want other modules for data science, I recommend Anaconda Python.https://realpython.com/courses/python-linear-regression/continue/#t=199.48
03:25https://realpython.com/courses/python-linear-regression/continue/#t=205.09
I’m going to be using Jupyter in this course.https://realpython.com/courses/python-linear-regression/continue/#t=205.09
So if you’re not familiar with Jupyter,https://realpython.com/courses/python-linear-regression/continue/#t=207.61
you can go ahead and check out this Real Python course on how to use Jupyter.https://realpython.com/courses/python-linear-regression/continue/#t=209.35
03:34https://realpython.com/courses/python-linear-regression/continue/#t=214.33
But if you’re more comfortable with using your own editor, it’s perfectly fine.https://realpython.com/courses/python-linear-regression/continue/#t=214.33
You’ll have no problems following along. And one more note,https://realpython.com/courses/python-linear-regression/continue/#t=218.65
the code in this course has been tested in Python 3.9,https://realpython.com/courses/python-linear-regression/continue/#t=222.97
but even if you have slightly older versions of Python, you should be all right.https://realpython.com/courses/python-linear-regression/continue/#t=226.33
03:51https://realpython.com/courses/python-linear-regression/continue/#t=231.99
Here’s the table of contents of the course.https://realpython.com/courses/python-linear-regression/continue/#t=231.99
We’re going to begin by taking a look at simple linear regression.https://realpython.com/courses/python-linear-regression/continue/#t=234.27
This is linear regression where we only have one input variable.https://realpython.com/courses/python-linear-regression/continue/#t=238.23
04:02https://realpython.com/courses/python-linear-regression/continue/#t=242.07
Then we’ll move on to multiple linear regression and then tackle polynomialhttps://realpython.com/courses/python-linear-regression/continue/#t=242.07
regression, both for the simple case and for the multiple input case.https://realpython.com/courses/python-linear-regression/continue/#t=246.96
And then we’ll wrap things up in a summary. All right.https://realpython.com/courses/python-linear-regression/continue/#t=251.49
04:14https://realpython.com/courses/python-linear-regression/continue/#t=254.85
I hope you’re looking forward to the course. Let’s get going then.https://realpython.com/courses/python-linear-regression/continue/#t=254.85
Dec. 12, 2023https://realpython.com/courses/python-linear-regression/continue/#comment-72e9fa3a-2cf2-43e3-86f5-589010136a5d
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Overviewhttps://realpython.com/courses/python-linear-regression/
https://realpython.com/videos/simple-linear-regression-background/
Starting With Linear Regression in Python (Overview) 04:19 https://realpython.com/videos/python-linear-regression-overview/
Simple Linear Regression: Background 05:46 https://realpython.com/videos/simple-linear-regression-background/
Simple Linear Regression: Code 06:57 https://realpython.com/lessons/simple-linear-regression-code/
Multiple Linear Regression: Background 05:01 https://realpython.com/lessons/multiple-linear-regression-background/
Multiple Linear Regression: Code 04:59 https://realpython.com/lessons/multiple-linear-regression-code/
Polynomial Regression: Background 07:47 https://realpython.com/lessons/polynomial-regression-background/
Simple Polynomial Regression: Code 06:35 https://realpython.com/lessons/simple-polynomial-regression-code/
Multiple Polynomial Regression: Code 04:36 https://realpython.com/lessons/multiple-polynomial-regression-code/
Linear Regression in Python (Quiz) 06:30 https://realpython.com/lessons/linear-regression-in-python-quiz/
Starting With Linear Regression in Python (Summary) 00:53 https://realpython.com/lessons/python-linear-regression-summary/
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