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lets use ml to fight disease, especially cancer

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lets use ml to fight disease, especially cancer
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# This file is part of pylastfp.
# Copyright 2010, Adrian Sampson.
#
# pylastfp is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# pylastfp is distributed in the hope that it will be useful,
@dexterous
dexterous / truth.clj
Last active January 6, 2016 21:30
The truth about dynlangs
#!/usr/bin/env lein-exec
(println (group-by (fn [e] (if e true false)) [true, false, -1, 0, 1, 2, nil, (new Object), [], #{}, '(), [(new Object)], {}, {:foo, (new Object)}]))
;;{true [true -1 0 1 2 #<Object java.lang.Object@4d8ce14a> [] #{} () [#<Object java.lang.Object@48ff4cf>] {} {:foo #<Object java.lang.Object@7114460>}], false [false nil]}
@christiangenco
christiangenco / videos.js
Created March 28, 2012 11:24 — forked from csabapalfi/videos.js
Download and Organize Coursera videos
$("h3.list_header").each(function(sectionIndex){
var sectionName = $(this).text().replace(/Chapter .+ - /,"").replace(/\:/,'-').replace(/^(V|I|X)+\. /,'');
$(this).parent().next().find("a.lecture-link").each(function(videoIndex){
var $lectureLink = $(this);
var videoName = $.trim($lectureLink.text());
var downloadLink = $lectureLink.attr('href').replace('view','download.mp4');
var cookieHeader = ' --header \"Cookie:'+ document.cookie + '\" ';
var directory = (sectionIndex+1) + '. ' + sectionName + '/';
var filename = directory + (videoIndex+1) + '. ' + videoName + '.mp4';
@erikh
erikh / hack.sh
Created March 31, 2012 07:02 — forked from DAddYE/hack.sh
OSX For Hackers
#!/usr/bin/env sh
##
# This is script with usefull tips taken from:
# https://github.com/mathiasbynens/dotfiles/blob/master/.osx
#
# install it:
# curl -sL https://raw.github.com/gist/2108403/hack.sh | sh
#
@a34729t
a34729t / RunStanfordParser.java
Created April 30, 2012 21:15
Programmatic interaction with Stanford Parser- using built in tokenization and using an external tokenizer
package foo;
import edu.stanford.nlp.fsm.ExactGrammarCompactor;
import edu.stanford.nlp.io.IOUtils;
import edu.stanford.nlp.io.NumberRangeFileFilter;
import edu.stanford.nlp.io.NumberRangesFileFilter;
import edu.stanford.nlp.ling.*;
import edu.stanford.nlp.objectbank.TokenizerFactory;
import edu.stanford.nlp.parser.ViterbiParser;
import edu.stanford.nlp.parser.KBestViterbiParser;
@yanofsky
yanofsky / LICENSE
Last active October 17, 2024 22:49
A script to download all of a user's tweets into a csv
This is free and unencumbered software released into the public domain.
Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.
In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
'''
x = 'Writing Fast Tests Against Enterprise Rails 60min \n Overdoing it in python 45min'
print x
y = x.split()
print y
'''
import re
def login():
import wx
from send_pass import send_pwd
class AP_App(wx.App):
def OnInit(self):
frame = AP_MainFrame ("Test application", (0, 0), (650, 350))
# frame.Show()
@debasishg
debasishg / gist:8172796
Last active November 11, 2024 07:10
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&amp;rep=rep1&amp;t
@staltz
staltz / introrx.md
Last active November 19, 2024 09:32
The introduction to Reactive Programming you've been missing