Linear Regression vs Logistic Regression - What's The Difference?

Whether it's predicting the stock market, estimating the likelihood of a customer churning, or even guessing the type of fruit based on its color and shape, regression is a powerful tool in the data scientist's toolbox.
Linear regression can be applied to a wide range of problems where the goal is to predict a continuous outcome based on one or more independent variables. For example, you could use linear regression to predict the price of a house based on its size, location, and other factors.
Logistic regression, on the other hand, is typically used to predict a binary outcome, such as success or failure, win or lose. It is particularly useful for classification problems, where the goal is to predict which of two or more classes a given input belongs to. For example, you could use logistic regression to predict whether a customer will churn or not based on their behavior. You could also use it to predict whether an email is spam or not based on its content.

[@itstudent5824]

this video just summarized a week worth of studying and coding

[@MindyBrockdesigns]

How do you handle ignoring a column while building a regression model in python? I want to keep the ID field in the model so I can identify the prediction of churn, but it is causing overfitting and making the model not very accurate.

[@TomvanLint-p3r]

I'm trying to understand this. What has me puzzled about the explanation about linear regression is the relevance of the locations as stated in 1:28. Why mention this when it's not part of the equation? On the other hand, the prices aren't only dependable on the size. Where does the location information goes in the schematic because you only have 2 variables? Aren't you comparing apples and oranges? I apologize if these are silly questions, but I can't wrap my head around this.

[@user-fq2eh7gl9e]

Thanks very clear and informative 👍🏻

[@shayw2329]

Awesome video, thank you!!

[@marubirhanu7527]

my sweat

[@kauthrahntabadde-sz2bo]

Thanks for the video. Why does linear regression use a t test and logistic regression a z test ?

[@PeaceCalm42]

Great video simple n easy

[@user-fq2eh7gl9e]

What does customer turn on mean ?????

[@enchanter7871]

I was wondering that too. I keep hearing the "the customer churns" ???

[@enchanter7871]

"Churn rate is the percentage of customers who end their relationship with a company within a given period" found it lol

[@stefc304]

I love the Krispy Kreme background!

[@muhammedfuatnuroglu3025]

Great, thanks for the video.

[@moneymc6470]

That fruitless joke turned my smile upside down😂😂😂

[@JohnJohnson-wm7it]

Hold up, this isn't a brewing video

[@I-used-to-be-orcaz]

i like ur shirt

[@WiiHack]

good video, would remove the background music tho

[@samirelzein1095]

Spoke a lot to say nothing