Topic: wharton Goto Github
Some thing interesting about wharton
Some thing interesting about wharton
wharton,Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)
User: dobriban
wharton,Builds Google Sheet (600+ visits) with course and instructor evaluations and clearing prices distributed from the Wharton Analytics Club; visualization to help select courses
User: jrfarrer
Home Page: http://bit.ly/cousematch_build_f17
wharton,Builds Google Sheet (650+ visits) with course and instructor evaluations and clearing prices distributed from the Wharton Analytics Club; visualization to help select courses
User: jrfarrer
Home Page: http://bit.ly/coursematch_build_s18
wharton,Assisted Wharton professors with data analysis for a paper on the changing of brand value over time
User: jrfarrer
Home Page: https://jrfarrer.github.io/dynamic_brand_equity/
wharton,A lecture on the basics of exploratory data analysis using tidyverse as a TA for Wharton's Statistics Department's STAT701 - Modern Data Mining.
User: jrfarrer
Home Page: http://bit.ly/stats_eda
wharton,Shiny mobile app that has users select whether headlines are real or fake (from Buzzfeed survey); connects to mysql DB on EC2
User: jrfarrer
Home Page: https://jordanfarrer.shinyapps.io/fake_news/
wharton,Perpetuities, annuities, and yield to maturity on corporate bonds
User: jrfarrer
wharton,Diversification, efficient portfolios, capital market line, and CAPM
User: jrfarrer
wharton,CAPM with Dell stock
User: jrfarrer
Home Page: https://jrfarrer.github.io/fnce611_hw4/
wharton,Forecasting customer retention using the beta-geometric model
User: jrfarrer
wharton,Modeling count data using the negative binomial distribution
User: jrfarrer
wharton,Brand concentration using count models; means and zeroes and method of moments estimation
User: jrfarrer
wharton,Modeling choice data with the beta-binomial and Empirical Bayes
User: jrfarrer
wharton,Timing models such as the exponential-gamma to measure time to purchase
User: jrfarrer
wharton,Discounted expected residual lifetime value using the Beta-discrete-Weibull; integrated models such as BG/BB
User: jrfarrer
Home Page: https://jrfarrer.github.io/mktg776_hw6/
wharton,Latent-class count models using the NBD and Poisson
User: jrfarrer
Home Page: https://jrfarrer.github.io/mktg776_hw7/
wharton,Applying NBD count models to examine the behavior of Wharton MBA students on the messaging platform GroupMe
User: jrfarrer
Home Page: https://jrfarrer.github.io/mktg776_p1/
wharton,Implement timing model that will predict Dish Networkโs subscriber acquisition in 2017
User: jrfarrer
Home Page: https://jrfarrer.github.io/mktg776_p2/
wharton,A homework assignment from Seth Stephens-Davidowitz's class called Understanding Behavior with Big Data
User: jrfarrer
wharton,Linear regression using different variable selection techniques
User: jrfarrer
Home Page: https://jrfarrer.github.io/stat701_hw1/
wharton,Classification using logistic regression and model selection criteria
User: jrfarrer
Home Page: https://jrfarrer.github.io/stat701_hw2
wharton,Regularization using LASSO and ridge regression; cross-validation for parameter selection
User: jrfarrer
Home Page: https://jrfarrer.github.io/stat701_hw3/
wharton,Text classification using logistic regression, SVM, and random forest; PCA
User: jrfarrer
Home Page: https://jrfarrer.github.io/stat701_hw4/
wharton,Building a model to predict whether or not a patient would be readmitted within 30 days after diabetic hospitalization
User: jrfarrer
Home Page: https://jrfarrer.github.io/stats701_miniproject/
wharton,Github Action wrapper for the Jake Wharton's dependency-tree-diff tool
Organization: usefulness
Home Page: https://medium.com/@cycki/surfacing-pull-request-hidden-changes-but-for-lazy-people-196d825519c9
wharton,Github Action wrapper for the Jake Wharton's Diffuse library
Organization: usefulness
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.