![]() The line which best fits is called the Regression line. Now, we have to find a line that fits the above scatter plot through which we can predict any value of y or response for any value of x for n observations (in above example, n=10).Decision Tree Introduction with exampleįor understanding the concept let’s consider a salary dataset where it is given the value of the dependent variable(salary) for every independent variable(years experienced).Removing stop words with NLTK in Python.Regression and Classification | Supervised Machine Learning.Basic Concept of Classification (Data Mining).Gradient Descent algorithm and its variants.ML | Momentum-based Gradient Optimizer introduction.Optimization techniques for Gradient Descent.ML | Mini-Batch Gradient Descent with Python.Difference between Batch Gradient Descent and Stochastic Gradient Descent.Difference between Gradient descent and Normal equation.ML | Normal Equation in Linear Regression. ![]() Mathematical explanation for Linear Regression working.Linear Regression (Python Implementation). ![]()
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