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목록Deep Learning (3)
My Progress
[Supervised ML] Classification with logistic regression - 8
1. IntuitionLinear Regression is not a good method for Classification Problem.Why?One outlier on the right changes the linear regression function. It moves decision boundary dramatically. 2. Logistic Regression2.1 FormulaLogistic function allows the function to be curved unlike the linear regression. This is a sigmoid function aka logistic function. x-axis represents the number z. It outputs a v..
[Supervised ML] Feature scaling - 5
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 ..
[Supervised ML] Regression/ Cost function - 2
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 =..