Michael Galarnyk mGalarnyk

PCA Application	Step by Step Jupyter Notebook (.ipynb)	Pipeline
Visualization	Without Pipeline (.ipynb)	Pipeline
Speeding Up Machine Learning Algorithms	Without Pipelines (.ipynb)	Pipeline

Developing Data Products Week 1 Quiz 1 John Hopkins Coursera

Github repo for the Course: Developing Data Products John Hopkins (Coursera)
Quiz Needs to be viewed here at the repo (because the questions and some image solutions cant be viewed as part of a gist)

Question 1

True or False | Statement

Operating System	Blog Post	Youtube Video
Mac	Install Anaconda on Mac	Youtube Video
Windows	Install Anaconda on Windows	Youtube Video
Ubuntu	Install Anaconda on Ubuntu	Youtube Video
All	Environment Management with Conda (Python 2 + 3, Configuring Jupyter Notebooks)	Youtube Video

Machine Learning Week 6 Quiz 2 (Machine Learning System Design) Stanford Coursera

Github repo for the Course: Stanford Machine Learning (Coursera)
Quiz Needs to be viewed here at the repo (because the questions and some image solutions cant be viewed as part of a gist)

Question 1

Statistic | Solution

	import numpy as np
	import pandas as pd
	term = 60
	P = 34689.96
	def calc_interest(P,emi,interest_rate = 0.0702):
	interest_paid = np.floor(((interest_rate/12)P)100)/100
	principal_paid = np.round(emi-interest_paid, 2)
	new_balance = np.round(P - principal_paid,2)
	return(emi, interest_paid, principal_paid, new_balance)

	P = 34689.96
	term = 60

	def generate_loan_table(P, term, interest_rate=0.0702):

	def calc_emi(P, n, interest_rate):
	r = interest_rate / 12
	numerator = (r ((1 + r)*(n)) )
	denominator = ((1 + r)**(n)) - 1
	emi = P * (numerator / denominator)

	us_state_abbrev = {
	'Alabama': 'AL',
	'Alaska': 'AK',
	'Arizona': 'AZ',
	'Arkansas': 'AR',
	'California': 'CA',
	'Colorado': 'CO',
	'Connecticut': 'CT',
	'Delaware': 'DE',
	'Florida': 'FL',

	start_urls = ["https://fundrazr.com/find?category=Health"]

	npages = 2

	# This mimics getting the pages using the next button.
	for i in range(2, npages + 2 ):
	start_urls.append("https://fundrazr.com/find?category=Health&page="+str(i)+"")

	for href in response.xpath("//h2[contains(@class, 'title headline-font')]/a[contains(@class, 'campaign-link')]//@href"):
	# add the scheme, eg http://
	url = "https:" + href.extract()