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1. What is Feature Engineering? Using intuition to design new features, by transforming or combinging original features. Example) House price. If we are given the dimension of the house such as length and width, we can create a new variable to include for price prediction of a house. For example, we create a area variable with length and width. 2. Feature engineering in Polynomial Regression We ..

1. Intuition House example: Lets say we are predicting the price of a house based on its size and number of bed rooms. Number for size of a house is relatively larger than the number of bed rooms. This large difference between numbers will make it hard to accurately predict the price. How is this related to gradient descent? Since the number for size is large, it takes smaller w value to make a ..

1. Linear Regression Purpose: To predict the output based on the given examples or dataset 1. 1 Terminology Univariate linear regression: Linear regression with one(single feature x) variable fw,b(x) = wx + b 1.2 Code Necessary Libraries #Numpy, a popular library for scientific computing import numpy as np #Matplotlib, a popular library for plotting data import matplotlib.pyplot as plt x_train =..