Publications by Amber Ferger
DATA 612: Project 2 | Content Based and Collaborative Filtering
Project Instructions 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.For assignment 2, start with an existing dataset of user-item ratings, such MovieLens. Implement at least two of these recommendation algorithms: Content-Based Filtering Us...
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DATA 612: Final Project Planning Doc
Assignment Find an interesting dataset and describe the system you plan to build out. If you would like to use one of the datasets you have already worked with, you should add a unique element or incorporate additional data. (i.e. explicit features you scrape from another source, like image analysis on movie posters). The overall goal, however, ...
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DATA 612: Project 5 | Implementing a Recommender System on Spark
Assignment 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 ...
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DATA 612: Research Discussion 4
Mitigating the Harm of Recommender Systems Read one or more of the articles below and consider how to counter the radicalizing effects of recommender systems or ways to prevent algorithmic discrimination. Renee Diresta, Wired.com (2018): Up Next: A Better Recommendation System Zeynep Tufekci, The New York Times (2018): YouTube, the Great Radical...
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DATA 608 – Knowledge and Visual Analytics: Assignment 1
Principles of Data Visualization and Introduction to ggplot2 I have provided you with data about the 5,000 fastest growing companies in the US, as compiled by Inc. magazine. lets read this in: inc <- read.csv("https://raw.githubusercontent.com/charleyferrari/CUNY_DATA_608/master/module1/Data/inc5000_data.csv", header= TRUE) And lets preview this...
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DATA 612: Project 3 | MATRIX FACTORIZATION METHODS
Assignment 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 welco...
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DATA 612: Research Discussion 3
Algorithmic Bias As more systems and sectors are driven by predictive analytics, there is increasing awareness of the possibility and pitfalls of algorithmic discrimination. In what ways do you think Recommender Systems reinforce human bias? Reflecting on the techniques we have covered, do you think recommender systems reinforce or help to preven...
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DATA 612: Project 4 | Accuracy and Beyond
Assignment The goal of this assignment is give you practice working with accuracy and other recommender system metrics.In this assignment you’re asked to do at least one or (if you like) both of the following: Work in a small group, and/or Choose a different dataset to work with from your previous projects. Deliverables As in your previous a...
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DATA 612: Health Recommender Systems
Recommender Systems In Context: Health Recommender SystemsAmber Ferger6/30/2020 What is an HRS? Health Recommender System Provides recommendations on diagnosis/treatment given diagnosis search The Problem with self-searches Findability, Comprehendability, Reliability The Solution: Personalized Health Recommendation Systems Personalized bas...
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DATA 612: Final Project
Load Libraries Project Goals & Methodology The overall goal of this project is to build a recommender system that predicts joke ratings. Although we initially aimed to use spark on databricks, we ran into a number of challenges that prevented us from continuing. Instead, we have chosen to create a recommender that is based on a more advanced tec...
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