Regression is a supervised learning technique that aids in the discovery of variable correlations and allows us to forecast a continuous output variable using one or more predictor variables.
Regression Linear:
In Machine Learning, it is one of the most widely used regression algorithms. To anticipate the output variables, a significant variable from the data set is picked (future values).
Financial forecasting, trend analysis, marketing, time series prediction, and even drug response modelling are all applications of regression models. Linear regression, regression trees, lasso regression, and multivariate regression are some of the most used forms of regression methods.
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Rishu Shrivastav
5
explained everything in detail. I have a question learnvern provide dataset , and ppt ? or not?
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VIKAS CHOUBEY
5
very nicely explained
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Vrushali Kandesar
5
Awesome and very nicely explained!!!
One importing thing to notify to team is by mistakenly navie's practical has been added under svm lecture and vice versa (Learning Practical 1)
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Mohd Mushraf
5
Amazing Teaching
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Juboraj Juboraj
5
Easy to understand & explain details.
J
Joydeb
5
Awesome Course sir and your teaching style is very GOOD.
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Shaga Chandrakanth Goud
5
Hi Kushal ji, Thanks a lot for a very good explanation. I have doubts about where we can get the dataset that you explained in the video. Can you make it available in resource ,so that we can downld
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Neel Khairnar
5
Kushal is very good explainer he is covering all topics nicely 👍
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