Alican Akca AlicanAKCA

Machine Learning Week 1 Quiz 2 (Linear Regression with One Variable) Stanford Coursera

Github repo for the Course: Stanford Machine Learning (Coursera)

Question 1

Consider the problem of predicting how well a student does in her second year of college/university, given how well she did in her first year.

Specifically, let x be equal to the number of "A" grades (including A-. A and A+ grades) that a student receives in their first year of college (freshmen year). We would like to predict the value of y, which we define as the number of "A" grades they get in their second year (sophomore year).

	@author: Alican AKCA
	"""
	import pandas as pd #Kütüphaneleri ekledik!
	from sklearn.model_selection import train_test_split
	from sklearn.preprocessing import StandardScaler
	from sklearn.svm import SVC
	from sklearn.metrics import confusion_matrix

	veriler = pd.read_csv('Datasets.csv') # We have loaded our dataset. Note that it is located in the same directory.
	x = veriler.iloc[:,3:7].values # We will view our columns.

	#####################################################################################
	# Dec 16 2020 #
	# github.com/Alicanakca #
	#####################################################################################
	import requests
	import json
	from datetime import datetime
	from matplotlib import pyplot as plt

	x = [] #For dates : year-month-day

	# Dataset : https://raw.githubusercontent.com/tidyverse/ggplot2/master/data-raw/diamonds.csv
	# Alican AKCA - 20.01.2021

	#### Required Libraries

	# For Visualization and Calculation
	import matplotlib.pyplot as plt
	import matplotlib as mpl
	import matplotlib.pylab as pylab
	import seaborn as sns

	from matplotlib import pyplot as plt
	from random import randint
	num1 =0
	num2=0
	summary = 0
	mean = 0
	numberOfBeats = 0
	plt.title('')
	plt.ylabel('Mean')
	plt.xlabel('Number Of Beats')

	import random
	import json
	import pandas as pd
	import numpy as np
	import matplotlib.pyplot as plt
	import pandas as pd

	from sklearn.model_selection import train_test_split
	from sklearn.preprocessing import StandardScaler
	from sklearn.metrics import confusion_matrix