travisbrown

5663832,AliAsifPTI,277,IN
7071762,cdf,1319,ID
7316382,TheSuperFFreak,4455,ID
8056732,andresobreiro_,2531,ID
8671052,CPorgyUniverse,490837,ID
12883902,TaxWiser,111,TR
13140962,WildCuddler,30097,ID
14181996,kevincubschgo,953,ID
14231320,recentpoker,6088,RU
14331162,hekanaho,1296,TR

strengejacke

library(glmmTMB)
library(ggeffects)

data("Salamanders")
m1 <- glmmTMB(
  count ~ mined + (1 | site),
  zi =  ~ mined,
  family = poisson,
  data = Salamanders
)

adamlauretig

---
title: "Using Gensim in R"
author: "Adam Lauretig"
date: "3/17/2018"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

jaeddy

Building a new RStudio Server AMI

The steps below can be followed to create a new AMI for use with Amazon EC2 instances that includes the latest versions of R, RStudio, and RStudio Server. The idea is inspired by the work of Louis Aslett, who creates and hosts his own public AMIs for RStudio. My own goal was to create an AMI with RStudio v1.0.0 or higher, such that I could use the recent R Notebooks feature. However, the instructions should generally apply for whenever you might be impatient accessing the latest version of R-related software on AWS (via an interactive browser interface...).

Getting started

1. Create a new EC2 instance with the latest Ubuntu AMI (should be fine to do with Spot); based on Louis Aslett's AMI, I opted to include a general purpose SSD EBS volume with 10GB of storage space
2. SSH into the instance

Downloading/installing RStudio Server

tjvananne

#' A word vector is a giant matrix of words, and each word contains a numeric array that represents the semantic
#' meaning of that word. This is useful so we can discover relationships and analogies between words programmatically.
#' The classic example is "king" minus "man" plus "woman" is most similar to "queen"


# function definition --------------------------------------------------------------------------

    # input .txt file, exports list of list of values and character vector of names (words)
    proc_pretrained_vec <- function(p_vec) {

rtt

Tinder API documentation

Note: this was written in April/May 2014 and the API may has definitely changed since. I have nothing to do with Tinder, nor its API, and I do not offer any support for anything you may build on top of this. Proceed with caution

http://rsty.org/

I've sniffed most of the Tinder API to see how it works. You can use this to create bots (etc) very trivially. Some example python bot code is here -> https://gist.github.com/rtt/5a2e0cfa638c938cca59 (horribly quick and dirty, you've been warned!)

hadley

.Rproj.user
.Rhistory
.RData
*.Rproj
*.html

bobthecat

require(inline)
require(RcppArmadillo)

## extract cosine similarity between columns
cosine <- function(x) {
    y <- t(x) %*% x
    res <- 1 - y / (sqrt(diag(y)) %*% t(sqrt(diag(y))))
    return(res)
}