stephanieleevillanueva Goto Github PK
Name: Stephanie Lauren Lee Villanueva
Type: User
Company: Sotera Defense Solutions
Location: Seattle, WA
Stephanie Lauren Lee Villanueva's Projects
classification_and_d3
Predicting hypertension using classification algorithms and basic visualization of results using d3
correlation-approximation
Spark implementation of the Google Correlate algorithm to quickly find highly correlated vectors in huge datasets
cyberdatamunging
Cyber security data munging
d3-book
Sample code files to accompany the book “Interactive Data Visualization for the Web”
distributed-graph-analytics
Distributed Graph Analytics (DGA) is a compendium of graph analytics written for Bulk-Synchronous-Parallel (BSP) processing frameworks such as Giraph and GraphX. The analytics included are High Betweenness Set Extraction, Weakly Connected Components, Page Rank, Leaf Compression, and Louvain Modularity.
ds4_benson
Metis Project - MTA analysis
dsp
Metis prework for ds4 cohort
jquery-nstslider
Nestoria Sliders jQuery Plugin
json2avro
Fast JSON to Avro converter
marriage-vs-workforce
Visualization and analysis of the workforce of married couples
meetup-member-recommender
Using Meetup data to make Meetup network recommendations
nlp_nltk_mongodb
Utilizing NLP/nltk to build a simple vegas hotel recommendation app using guest reviews' sentiments
old_blog
My Metis Chronicles
otx-python-sdk
Open Threat Exchange is an open community that allows participants to learn about the latest threats, research indicators of compromise observed in their environments, share threats they have identified, and automatically update their security infrastructure with the latest indicators to defend their environment.
pandasql
sqldf for pandas
progressbar-python3
Fork of python-progressbar http://code.google.com/p/python-progressbar/source/browse/#hg
python-linkedin
Python interface to the LinkedIn API
sotera
Learning big data
stephanieleevillanueva.github.io
My Metis Chronicles
topics
Topic modeling with gensim and LDA
tv_scraping_regressions
Web scraping using BeautifulSoup and data analysis using Statsmodels and Scikit.
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