amy-aboughazy Goto Github PK

alteryxrplugingui.r

Reskin R Tool

android-app-development

This repository contains all the source code examples and the FAQ for our Android App Development Specialization for Coursera

android-basics-kotlin-birthday-card-app-solution

android-basics-kotlin-birthday-card-with-image-app-solution

android_guides

Extensive Open-Source Guides for Android Developers

androidbeginners-lesson1

course-js-and-the-dom

coursera-java-for-android

Coursera java for android MOOC Course

create-an-analytical-dataset

This is a project made for Udacity's Predictive Analytics for business Nanodegree program with the goal of cleaning and preparing data for analysis.

create-an-analytical-dataset-1

2nd project of my Udacity Predictive Analytics for Business

create-an-analytical-dataset-2

The Business Problem Pawdacity is a leading pet store chain in Wyoming with 13 stores throughout the state. This year, Pawdacity would like to expand and open a 14th store. Your manager has asked you to perform an analysis to recommend the city for Pawdacity’s newest store, based on predicted yearly sales. Your first step in predicting yearly sales is to first format and blend together data from different datasets and deal with outliers. Your manager has given you the following information to work with: The monthly sales data for all of the Pawdacity stores for the year 2010. NAICS data on the most current sales of all competitor stores where total sales is equal to 12 months of sales. A partially parsed data file that can be used for population numbers. Demographic data (Households with individuals under 18, Land Area, Population Density, and Total Families) for each city and county in the state of Wyoming. For people who are unfamiliar with the US city system, a state contains counties and counties contains one or more cities. Map of Wyoming Counties Steps to Success Step 1: Business and Data Understanding Your project should include a description of the key business decisions that need to be made. Step 2: Building the Training Set To properly build the model, and select predictor variables, create a dataset with the following columns: City 2010 Census Population Total Pawdacity Sales Households with Under 18 Land Area Population Density Total Families This dataset will be your training set to help you build a regression model in order to predict sales in the Practice Project in the next lesson. Every row should have sales data because we're trying to predict sales. Notes You should be consolidating the data at the city level and not at the store level. We only have data at the city wide level so any analysis at the store level will not be sufficient to complete this analysis. We simply need to focus on cleaning up and blending the data together in this step. If you’ve done everything correctly, the sum for each of the above columns should be: Census Population: 213,862 Total Pawdacity Sales: 3,773,304 Households with Under 18: 34,064 Land Area: 33,071 Population Density: 63 Total Families: 62,653 with 11 rows of data

create-an-analytical-dataset-alteryx

Project Overview You are a loan officer at a young and small bank (been in operations for two years) that needs to come up with an efficient solution to classify new customers on whether they can be approved for a loan or not. You'll use a series of classification models to figure out the best model and provide a list of creditworthy customers to your manager.

fend

General Front End Nanodegree Content Resources

fullstack-course4

Example code for HTML, CSS, and Javascript for Web Developers Coursera Course

happy-birthday

The official repository for the first Android Development for Beginners App : Happy Birthday

hello-world

A new repository

javaandroid

javascript-essential-training-2832077

JavaScript Essential Training

just-java

The official repository for the second Android Development for Beginners App : Just Java

learning-java-2825378

Learning Java (REVISION Q1 2020)

learning-sql-548044

Learning SQL Programming

material-components-android-codelabs

Codelabs for Material Components for Android (MDC-Android)

meta-coursera-programming-with-javascript

my-travel

my-travel-plans

nd064_course_1

predicting-catalog-demand

Project 1.2 : The company sent out its first print catalog last year and now its planning to send again print catalog to new 250 customers from their mailing list. Determine how much profit can company expect to earn from this. Management does not want to send the catalog out to these new customers unless the expected profit contribution exceeds $10,000. So the task is to predict the estimated profit if catalog is sent to new customers.

predictive-analytics-for-business

Contains Coursework from the Udacity Nanodegree

predictive-analytics-for-business-1

Udacity nanodegree

predictive-analytics-for-business-nanodegree

Kai Sheng Teh - Udacity Predictive Analytics for Business Nanodegree