Simple Linear Regression Algorithm Indepth Maths Intuition With Notes In Hindi

Linear Regression is the Most simple yet an Efficient machine learning algorithm So, you landed up here after scavenging over the internet to understand Line...

Krish Naik Hindi379.5K views52:20

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Linear Regression is the Most simple yet an Efficient machine learning algorithm So, you landed up here after scavenging over the internet to understand Linear Regression and I must say that your search ends here. So without further waiting, let us just jump to it. “Generalisation is the ultimate goal of any machine learning algorithm” Two major types of problems that machine learning algorithms try to solve are: Regression — Predict continuous value of a given data point Classification — Predict the class of the given data point Linear Regression, intuitively is a regression algorithm with a Linear approach. We try to predict a continuous value of a given data point by generalising on the data that we have in hand. The linear part indicates that we are using a linear approach in generalising over the data. Materials github : https://github.com/krishnaik06/Machine-Learning-Algorithms-Materials/tree/main ML Playlist: https://www.youtube.com/playlist?list=PLTDARY42LDV7WGmlzZtY-w9pemyPrKNUZ ---------------------------------------------------------------------------------------------------------------------------------------------------------------- Please donate if you want to support the channel through GPay UPID, Gpay: krishnaik06@okicici ----------------------------------------------------------------------------------------------------------------------- Recording Gears That I Use https://shorturl.at/wzI68 --------------------------------------------------------------------------------------------------------------------------- #krish #datasciencebusted #dataanalyst Connect with me here: Twitter: https://twitter.com/Krishnaik06​ Facebook: https://www.facebook.com/krishnaik06​ instagram: https://www.instagram.com/krishnaik06

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379.5K

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52:20

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Feb 5, 2022

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