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View LARS.py
from torch.optim.optimizer import Optimizer, required
class LARS(Optimizer):
def __init__(self, params, lr=required, momentum=0, dampening=0,
weight_decay=0, nesterov=False, eta=0.001):
if lr is not required and lr < 0.0:
raise ValueError("Invalid learning rate: {}".format(lr))
if momentum < 0.0:
raise ValueError("Invalid momentum value: {}".format(momentum))
View jscosine.js
function termFreqMap(str) {
var words = str.split(' ');
var termFreq = {};
words.forEach(function(w) {
termFreq[w] = (termFreq[w] || 0) + 1;
});
return termFreq;
}
function addKeysToDict(map, dict) {
View basicmap.r
doInstall <- TRUE
toInstall <- c("maps", "ggplot2")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)
library(ggplot2)
library(maps)
Prison <- read.csv("http://www.oberlin.edu/faculty/cdesante/assets/downloads/prison.csv")
head(Prison)
View rank_metrics.py
"""Information Retrieval metrics
Useful Resources:
http://www.cs.utexas.edu/~mooney/ir-course/slides/Evaluation.ppt
http://www.nii.ac.jp/TechReports/05-014E.pdf
http://www.stanford.edu/class/cs276/handouts/EvaluationNew-handout-6-per.pdf
http://hal.archives-ouvertes.fr/docs/00/72/67/60/PDF/07-busa-fekete.pdf
Learning to Rank for Information Retrieval (Tie-Yan Liu)
"""
import numpy as np
anonymous
anonymous / gs_sp_to_txt.sh
Created Jun 30, 2012
Google Speech to Text script
View gs_sp_to_txt.sh
arecord -D plughw:1,0 -f cd -t wav -d 3 -r 16000 | flac - -f --best --sample-rate 16000 -o out.flac; wget -O - -o /dev/null --post-file out.flac --header="Content-Type: audio/x-flac; rate=16000" http://www.google.com/speech-api/v1/recognize?lang=en | sed -e 's/[{}]/''/g'| awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]; exit }' | awk -F: 'NR==3 { print $3; exit }'
View points.r
mid_range <- function(x) mean(range(x, na.rm = TRUE))
centres <- ddply(county_df, c("state", "county"), summarise,
lat = mid_range(lat),
long = mid_range(long)
)
bubbles <- merge(centres, unemp, by = c("state", "county"))
ggplot(bubbles, aes(long, lat)) +
geom_polygon(aes(group = group), data = state_df,
colour = "white", fill = NA) +