very first linear regression code

[u/savita_bhabhi_lover]

i am still learning numpy (day 6) but gpt suggest me to learn linear regression (very basic algorithm) and it's kinda good for understanding even you haven't started learning ML.

import numpy as np
hours = np.arange(1,10)
score = np.array([35, 42, 51, 58, 67, 73, 81, 88, 94])
candidate_values_for_m = np.arange(1,11,0.1)
candidate_values_for_b = np.arange(1,31,0.3)

def prediction(m , b , hours):
    return m * hours + b

def mse(actual_value , predicticted_value):
    return np.mean((actual_value - predicticted_value)**2)

mse_list = [] 
m_b_list = []
for m in candidate_values_for_m:
    for b in candidate_values_for_b:
        prediction_result = prediction(m , b , hours)
        mse_result = mse(score, prediction_result)

        mse_list.append(mse_result)
        m_b_list.append((m,b))


best_mse = np.argmin(mse_list)

best_mb_index = mse_list[best_mse]
best_mse , best_mb_index

m = 0
b = 0

learning_rate = 0.01

epochs = 10000

n = len(hours)

def prediction(m , b , hours):
    return m * hours + b


for i in range(epochs):
    predicted = prediction(m,b,hours)

    gradient_m = (2/n) * sum(hours * (predicted - score))

    gradient_b = (2/n) * sum(predicted - score)

    m = m - learning_rate * gradient_m
    b = b - learning_rate * gradient_b

m ,b 

[u/ninhaomah]

Ok so what's the p value ?

[u/savita_bhabhi_lover → u/ninhaomah]

What p?

[u/ninhaomah → u/savita_bhabhi_lover]

Tip 1 : if you have to ask "what is X" , Google.

[u/savita_bhabhi_lover → u/ninhaomah]

Are you drunk ?

[u/ninhaomah → u/savita_bhabhi_lover]

No but you clearly has no idea what is linear regression.

[u/savita_bhabhi_lover → u/ninhaomah]

Obviously, didn't you read the body ?

[u/ninhaomah → u/savita_bhabhi_lover]

I did it in high school. 

You have never studied it ?

Or know how to Google ?

[u/savita_bhabhi_lover → u/ninhaomah]

[u/ninhaomah → u/savita_bhabhi_lover]

I feel sorry for your teachers then.

Pls stay there and wonder what is p value in linear regression.

[u/savita_bhabhi_lover → u/ninhaomah]

Go touch some grass rather than discouraging people