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Filmfundr's Projects

itunes-pricewatcher icon itunes-pricewatcher

Reads in an array of iTunes collectionIDs & prices, checks the iTunes API for changes in price, and logs the result.

itunes-product-viewer icon itunes-product-viewer

iTunesProductViewer is a jQuery plug-in that allows you to display price, artwork, descriptions, etc, about an app, music, movie, or iBook, on the Apple Store, using the iTunes Search API.

itunespicker icon itunespicker

Discover, search and compare world rankings for apps, ibooks, movies, music videos and music from iTunes (and AppStore) in any available country.

jukebox icon jukebox

Code for the paper "Jukebox: A Generative Model for Music"

meetyourfood icon meetyourfood

Mashup of various Web APIs (Facebook, Yelp, Amazon, FatSecret, Twitter etc). Implemented sentiment analysis on Amazon products using Stanford NLP. View readme file for further details

nashville icon nashville

A wrapper and command line interface for querying the iTunes Store API

netflix icon netflix

A sample algorithm for DVD distribution to Netflix customers

recommeder-system-for-movies icon recommeder-system-for-movies

Applied SVM ( Support Vector Machine ) and K-Means algorithm to recommend users their preferred movies on the basis of similar users. Worked on RDF dataset to find features of movies for efficient recommendations. Tools used : Netbeans, RDF dataset, Movielen data for movies, Virtuoso server, Matlab

recoprod icon recoprod

Content based Recommender System which implements sentiment analysis(Naive Bayes,SVMs) on Amazon product reviews. Built in Python(Beautiful Soup,SciPy,NumPy,matplotlib),Java and RapidMiner

sentiment icon sentiment

Sentiment analysis using machine learning techniques.

sentiment-1 icon sentiment-1

Simple Twitter sentiment analysis and visualization with Node.js

sentimentanalysis-moviereviews icon sentimentanalysis-moviereviews

The projects takes a number of movie reviews from http://www.cs.cornell.edu/people/pabo/movie-review-data/ (polarity dataset v2.0 and an independent dataset) and using SVM, Naive Bayes, KNN algorithms analysis the sentiment behind that review to being either positive or negative. The prediction is then compared to the actual sentiment behind the review and higher precision is targeted between all three algorithm. The research is then followed by a technical paper.

text-bot icon text-bot

Chat bot that uses Conversation and the Weather API

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