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This Logistic Regression video will help you understand how a Logistic Regression algorithm works in Machine Learning. You will learn what is Supervised Learning, what is a classification problem, and the maths behind Logistic Regression. In the end, you will see a demo on how to predict the number present in an image using Logistic Regression in Python.

Below topics are covered in this Logistic Regression Tutorial:
0:00 - 01:52 Introduction
01:52 - 05:35 What is Supervised Learning?
05:35 - 06:10 What is Classification?
06:10 - 15:49 What is Logistic Regression?
15:49 - 16:58 Comparing Linear and Logistic regression
16:58 - 18:40 Logistic regression applications
18:40 - 38:17 Use case - Predicting the number in an image


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What is Logistics Regression?
Logistic regression is a classification algorithm that is used to predict a binary outcome based on a set of independent variables. Logistic regression uses a logistic function to estimate the probability of a target variable belonging to a particular class or category. It assumes that the dependent variable is binary or dichotomous and there should be no or very little multicollinearity between the predictor variables. Logistic regression

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