luccabb

import time
import matplotlib.pyplot as plt

def insertionSort(array):
    steps = 0
    start = time.time()
    for a in range(1,len(array)):
        steps+=1
        key = array[a]
        b = a-1

shravanasati

import turtle, random
from math import *

t = turtle.Turtle()
turtle.bgcolor("black")

t.speed(3000000)

t.pensize(5)

ThePyProgrammer

import numpy as np

def convolve(image, kernel):
  # We start off by defining some constants, which are required for this code
  kernelH, kernelW = kernel.shape
  imageH, imageW = kernel.shape
  h, w = imageH + 1 - kernelH, imageW + 1 - kernelW
  
  # filter1 creates an index system that calculates the sum of the x and y indices at each point
  # Shape of filter1 is h x kernelW

Chiraagkv

def plot_histories(*args):
  '''
  Plots histories
  '''
  epochs1 = np.arange(1, len(pd.DataFrame(args[0].history)) + 1)
  fig, ax = plt.subplots(len(args), 2, figsize=(16, 7 * len(args)))
  fig.suptitle('Comparing Model Histories')
  for i in range(len(args)):
    loss1 = pd.DataFrame(args[i].history["loss"])
    ax[i, 0].set_title(f"Model {i + 1} Loss")

Chiraagkv

class LinearRegressor:
    def __init__(self, iters, X, y, lr):
        self.iters = iters
        self.X = X
        self.lr = lr
        self.y = y
        self.b = 0
        self.w = 1
    def hypothesis_function(self, x):
        list_of_hypothesis_functions = []