The goals / steps of this project are the following:
This is a very basic and simplistic collaborative filtering based recommender system. It uses a subset of the MovieLens dataset provided by GroupLens.
As of right now, the recommender generates a list of top 10 recommendations for any user in the dataset. Below are the steps on how it …
from numpy import exp, array, random, dot
# Define neural network class
class NeuralNetwork():
def __init__(self):
#Seed random number generator
random.seed(1)
# Model single neuron with 3 inputs and 1 output
# Assign random weights to a 3 x 1 matrix with values between -1 and 1
self.synaptic_weights = 2 …The goals / steps of this project are the following:
from numpy import *
def computer_error_for_line_given_points(b, m, points):
# Initialize error at 0
totalError = 0
# Loop through all points
for i in range(0, len(points)):
# Get x value
x = points[i, 0]
# Get y value
y = points[i, 0]
# Get squared difference and add to total error
totalError += (y - (m …The purpose of this exercise is to use deep neural networks to classify traffic signs. Specifically, we train a model to classify traffic signs from the German Traffic Sign Dataset.
The pickled data is a dictionary with 4 key/value pairs:
In this project, we use the following tools to identify lane lines on the road:
Color selection
Region of interest selection
Grayscaling
Gaussian smoothing
Canny Edge Detection
Hough Tranform line detection
We develop a pipeline on a series of individual images, and later apply …
read moreThis visualization describes the percentage of passengers that surived during the Titanic disaster. The circles represent the susbet of passengers categorized by sex, passenger class and point of embarkation. The size of the circle corresponds to the percent value; the higher the proportion of …
read moreThe goal of this project is to identify employees from Enron that have been in on the fraud committed that came to light in 2001. This will be based on a machine learning algorithm using public Enron financial and email information.
The dataset that will be used …
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#Load libraries
library(ggplot2)
library(lubridate)
library(dplyr)
library(tidyr)
library(gridExtra)
library(psych)
# Load the Data
data = read.csv('NYContributionData.csv', row.names = NULL)
#Convert dates from integers to DD-MM-YYYY format
data$contb_receipt_dt = dmy(data$contb_receipt_dt)
# Summarize the data set
dim(data)
## [1] 186976 18
names …Map Area: Waterloo, Ontario, Canada
Problems Encountered in the Map:
After initially downloading the Waterloo area and running it against the script below, I noticed the following problems with the data:
• Inconsistent methods of describing street direction (e.g. “N” or “North”)
• Inconsistent street types (e.g. St. instead …
# Import csv library
import unicodecsv
# Define function to read and store data
def read_csv(filename):
with open(filename, 'rb') as f:
reader = unicodecsv.DictReader(f)
return list(reader)
enrollments = read_csv('data/enrollments.csv')
daily_engagement = read_csv('data/daily_engagement.csv')
project_submissions = read_csv('data/project_submissions.csv')
# Print out first …A few researchers set out to determine the optimal length of chopsticks for children and adults. They came up with a measure of how effective a pair of chopsticks performed, called the "Food Pinching Performance." The "Food Pinching Performance" was determined by counting the number …
read moreThis script gathers ticker data on the tickers in the TickerList.csv file and calculates the following metrics:
- Simple moving averages
- RSI
- Exponential moving averages
- MACD
Then the tickers are filtered using the following user-defined parameters:
- MinPrice
- MaxPrice
- MinRSI
- MaxRSI
- MinVol
- MA1
- MA2
The technical charts of the tickers …
read moreThe Baseball Data was used to answer the following questions:
Are salaries higher in 2015 than in 1985?
Does the mean salary increase with the year?
Do a player salaries have a higher correlation with total runs or homeruns?
# Import packages
import csv
import numpy as np
import pandas as …