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RanaivosonHerimanitra / readme.md
Created April 7, 2017 05:46 — forked from baraldilorenzo/readme.md
VGG-19 pre-trained model for Keras

##VGG19 model for Keras

This is the Keras model of the 19-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

@RanaivosonHerimanitra
RanaivosonHerimanitra / readme.md
Created April 6, 2017 03:50 — forked from baraldilorenzo/readme.md
VGG-16 pre-trained model for Keras

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

@RanaivosonHerimanitra
RanaivosonHerimanitra / ReposContentsPerIssueOrPRevent.sql
Created February 16, 2017 14:21
Retrieve events (issues and PR) related to any contents of any repos for a given day (2015-01-01)
SELECT type,payload,repo_name,content,created_at FROM [githubarchive:day.20151001] x JOIN(
SELECT a.id,path,repo_name,content FROM (
SELECT * FROM (
SELECT a.id,path,repo_name,content FROM (
SELECT * FROM [bigquery-public-data:github_repos.files] WHERE path LIKE '%.java' ) a JOIN
(SELECT id,content FROM [bigquery-public-data:github_repos.contents]) b ON a.id=b.id
)
)
) c ON x.repo.name=a.repo_name HAVING type='PullRequestEvent' or type='IssueCommentEvent' LIMIT 5000
@RanaivosonHerimanitra
RanaivosonHerimanitra / github-mining.sql
Created January 21, 2017 14:46 — forked from thomasdarimont/github-mining.sql
Sample query for github dataset in big-query
SELECT
cont.sample_repo_name,
repo.watch_count
FROM
[bigquery-public-data:github_repos.sample_contents] as cont
JOIN [bigquery-public-data:github_repos.sample_repos] as repo
ON cont.sample_repo_name = repo.repo_name
WHERE
cont.content CONTAINS 'findbugs-maven-plugin</artifactId>'
AND cont.sample_path LIKE 'pom.xml'
library(shiny)
library(spdep)
library(leaflet)
library(RColorBrewer)
atx <- readRDS('travis.rds')
atx$id <- 1:nrow(atx)
atx2 <- atx[!is.na(atx$income), ]
---
title: "Introduction à R"
author: "Herimanitra R."
date: "17 octobre 2014"
output: html_document
---
<h1>Installation et presentation de l'interface</h1>
R est le logiciel de programmation statistique la plus complète et la plus fournie au monde.
Il contient des milliers de librairie ou package capable d’exécuter des taches spécifiques liées au domaine du calcul. De la bioinformatique à la Statistique en passant par l’économétrie, l’analyse numérique, la cartographie et le Data Mining.
import pandas
import rpy2.robjects as robjects
from rpy2.robjects.packages import importr
from rpy2.robjects.lib import grid
from rpy2.robjects.lib import ggplot2
## read in the distances to railroad (we calculated)
neardist = pandas.read_csv('data/NearDistance.csv')
## convert to R dataframe, via Python Dictionary data type
<!DOCTYPE html>
<html>
<head>
<meta name="viewport" content="width=device-width, initial-scale=1 " charset="UTF-8" >
<link rel="stylesheet" href="shared/jquery.mobile-1.4.2.min.css" />
<script src="shared/jquery.js" type="text/javascript"></script>
<script src="shared/jquery.mobile-1.4.2.min.js" type="text/javascript" > </script>
<script src="shared/shiny.js" type="text/javascript"></script>
<script src="shared/highcharts.js" type="text/javascript"></script>
<script src="shared/data.js" type="text/javascript"></script>
library(shiny)
# Define server logic for random distribution application
shinyServer(function(input, output,session) {
data <- reactive({
dist <- switch(input$dist,
norm = rnorm,
unif = runif,
lnorm = rlnorm,
exp = rexp,
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RanaivosonHerimanitra / impute2.cpp
Created January 22, 2014 17:54
improvement of the previous "impute" code :instead of doing the entire loop,index of missing rows have been already registered...
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]]
List modiframe2(DataFrame& df ) {
//nrow and ncol of the dataframe:
int nrow = df.nrows(), ncol= df.size() ;
double moy(0);
//define an empty list~dataframe
//List output(ncol)