Publications by Salma Elshahawy, Mael Illien, Dhairav Chhatbar
DATA607 Final Project
1 A Socio-Economic Investigation into Crime Presented by: Salma Elshahawy salma71 Dhairav Chhatbar dhairavc Mael Illien maelillien 1.1 Introduction This project provided us with the opportunity of showcasing many of the skills we have learned throughout this course and of applying them to an investigation into datasets of our choosing. We narro...
4845 sym R (1951 sym/11 pcs) 9 img 1 tbl
DATA607 Final Project (Draft)
1 A Socio-Economic Investigation into Crime 1.1 Introduction This project provided us with the opportunity of showcasing many of the skills we have learned throughout this course and of applying them to an investigation into datasets of our choosing. We narrowed our scope to a few datasets containing information on social economic information, n...
1252 sym R (6181 sym/20 pcs) 5 img 1 tbl
DATA607 Final Project (Draft)
1 A Socio-Economic Investigation into Crime Presented by: Salma Elshahawy [@salma71](https://github.com/salma71) Dhairav Chhatbar [@dhairavc](https://github.com/dhairavc) Mael Illien [@maelillien](https://github.com/maelillien) 1.1 Introduction This project provided us with the opportunity of showcasing many of the skills we have learned throug...
4330 sym R (1951 sym/11 pcs) 7 img 1 tbl
Data 606 - Data Project
Intro There are thousands of flights that fly within the inter-continental United States on a daily basis. Of these thousands of daily flights many are delayed, and it is these delays that cost the economy substantial financial loss. It would be of interest to understand if there is a pattern to the delays, then it would be of interest to airline...
7204 sym R (22831 sym/34 pcs) 17 img 2 tbl
DATA612: Recommender Systems - Project 2: Content-Based and Collaborative Filtering
library(dplyr) library(tidyr) library(kableExtra) library(scales) library(recommenderlab) library(ggplot2) The goal of this assignment is for you to try out different ways of implementing and configuring a recommender, and to evaluate your different approaches. Implement at least two of these recommendation algorithms: Content-Based Filteri...
3426 sym R (7150 sym/35 pcs) 11 img 2 tbl
DATA612: Project 3 - Matrix Factorization Methods
The goal of this assignment is give you practice working with Matrix Factorization techniques. Your task is implement a matrix factorization method—such as singular value decomposition (SVD) or Alternating Least Squares (ALS)—in the context of a recommender system. You may approach this assignment in a number of ways. You are welcome to start...
3017 sym R (7590 sym/22 pcs) 9 tbl
DATA612: Final Project- Proposal
library(recommenderlab) library(recommenderlabBX) library(ggplot2) library(dplyr) library(tidyr) library(data.table) library(kableExtra) General Goals For the final project for this course I would like to use the material learned in the course to build a recommendation model on the Book-Crossing Dataset. In determining the most appropriate...
1190 sym R (1701 sym/8 pcs) 22 img 2 tbl
DATA612: Recommender Systems - Research Discussion 2
For this discussion item, please watch the following talk and summarize what you found to be the most important or interesting points. The first half will cover some of the mathematical techniques covered in this unit’s reading and the second half some of the data management challenges in an industrial-scale recommendation system. http://www.yo...
2500 sym
DATA612: Project 5 - Implementing a Recommender System on Spark
The goal of this project is give you practice beginning to work with a distributed recommender system. It is sufficient for this assignment to build out your application on a single node. Adapt one of your recommendation systems to work with Apache Spark and compare the performance with your previous iteration. Consider the efficiency of the syst...
1422 sym R (2120 sym/9 pcs)
DATA612: Recommender Systems - Project 4: Accuracy and Beyond
The goal of this assignment is give you practice working with accuracy and other recommender system metrics As in your previous assignments, compare the accuracy of at least two recommender system algorithms against your offline data Implement support for at least one business or user experience goal such as increased serendipity, novelty, or di...
3458 sym R (3228 sym/12 pcs) 6 img