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# notice small alpha value | |
alpha = 0.0001 | |
iters = 1000 | |
# theta is a row vector | |
theta = np.array([[1.0, 1.0]]) |
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my_data = np.genfromtxt('data.csv', delimiter=',') # read the data | |
X = my_data[:, 0].reshape(-1,1) # -1 tells numpy to figure out the dimension by itself | |
ones = np.ones([X.shape[0], 1]) # create a array containing only ones | |
X = np.concatenate([ones, X],1) # cocatenate the ones to X matrix | |
y = my_data[:, 1].reshape(-1,1) # create the y matrix |
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import matplotlib.pyplot as plt | |
import numpy as np |
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//the function from before | |
function sum(number1, number2) { | |
console.log(number1 + number2); | |
} | |
//sum(2, 1); //3 | |
//new function that takes 3 parameters | |
function doesSomething(parameter1, parameter2, parameter3) { //again we define a function with 3 parameters | |
console.log('This is parameter 1: ',parameter1); //print parameter 1 | |
console.log('This is parameter 2: ',parameter2);//print parameter 2 |
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function sum (number1, number2){ //We defined a function with a name of sum and it takes 2 parameters | |
console.log (number1+number2); //Then it adds up the parameters and console.logs it | |
} | |
sum(2,1); //We invoke the function here and it prints out 3 |
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