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Showing posts with the label hypothesis function hypothesis testing in machine learning

Graphic design python turtle 🐢

By Kajal Vishwakarma -
from turtle import * import colorsys bgcolor('black') pensize(0) tracer(50) h=0 for i in range(300): c=colorsys.hsv_to_rgb(h,1,1) h+=0.9 color(c) forward(300) left(100) fd(i) goto(0,0) down() rt(90) begin_fill() circle(0) end_fill() rt(10) for j in range(5): rt(30) done() Please follow my blog and subscribe my channel for more videos and newly updates 👍👍👍👍👍 import turtle as t import colorsys t.bgcolor('black') t.tracer(100) h=0.4 def draw(ang,n): t.circle(5+n,60) t.left(ang) t.circle(5+n,60) for i in range(200): c=colorsys.hsv_to_rgb(h,1,1) h+=0.005 t.color(c) t.pensize(2) draw(90,i*2) draw(120,i*2.5) draw()
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Hypothesis function and testing in Machine Learning

By Kajal Vishwakarma -
 Hypothesis function and testing: - Hypothesis testing is a statistical method that is used in making statistical decision using experimental data. Hypothesis Testing is basically an assumption that we make about the population parameter. Ex : you say avg student in class is 40 or a boy is taller than girls. All those example we assume need some statistic way to prove those. we need some mathematical conclusion what ever we are assuming is true. Hypothesis testing is an essential procedure in statistics. A hypothesis test evaluates two mutually exclusive statements about a population to determine which statement is best supported by the sample data. When we say that a finding is statistically significant, it's thanks to a hypothesis test. The process of hypothesis testing is to draw inferences or some conclusion about the overall population or data by conducting some statistical tests on a For drawing some inferences, we have to make some assumptions that lead to two terms that ar
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