Chris Hokamp chrishokamp

## 5_word2vec.ipynb

      
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                chrishokamp
                / 5_word2vec.ipynb
            
            
              Created
              May 13, 2016 15:11
            
              
                Example solution to Udacity Deep Learning course assignment 5 -- W2V CBOW
              
          
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## working_memorization_example.ipynb

      
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                chrishokamp
                / working_memorization_example.ipynb
            
            
              Created
              August 6, 2015 16:12
            
              
                dataset shape is everything!
              
          
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## failed_memorization_example.ipynb

      
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                chrishokamp
                / failed_memorization_example.ipynb
            
            
              Created
              August 6, 2015 00:17
            
              
                A toy example testing the ability (or lack thereof) of a vanilla RNN to memorize sequence information
              
          
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## wmt15_word_level_qe_evaluation.py
from __future__ import division, print_function
import codecs
from sklearn.metrics import f1_score
import numpy as np
from argparse import ArgumentParser

import logging

logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
logger = logging.getLogger('wmt_eval_logger')

## hpt_rule_parse.ipynb

      
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                chrishokamp
                / hpt_rule_parse.ipynb
            
            
              Created
              February 5, 2015 13:43
            
              
                simple parsing of hpt rules into preauthoring autocomplete templates
              
          
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## grab_images.py
#!/usr/bin/python
#Author: Chris Hokamp
#Spring 2013

import sys
import requests
from BeautifulSoup import BeautifulSoup
import re

if len(sys.argv) != 4:

## fracking-puns.txt
fraternize
sassafras's
frankish
franjo
refractor
frannie
infractions
frantically
frankfurters
frantically

## sync_with_upstream.sh
# cd into your top level directory ml-group/

# add a remote called 'upstream'
git remote add upstream https://github.com/dcumachinelearning/ml-group.git
# pull from upstream
git pull upstream master
# push the new commits from upstream to your fork on github
git push

## install_anaconda.sh
# install the anaconda python distribution
echo 'grabbing the distro, note that you need to accept the license...'
wget https://3230d63b5fc54e62148e-c95ac804525aac4b6dba79b00b39d1d3.ssl.cf1.rackcdn.com/Anaconda-2.3.0-Linux-x86_64.sh
bash Anaconda*.sh
echo "all done, have a great day $USER"

## gensim_vector_space_notebook.json
{
 "metadata": {
  "name": "gensim_tutorial"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
	from __future__ import division, print_function
	import codecs
	from sklearn.metrics import f1_score
	import numpy as np
	from argparse import ArgumentParser

	import logging

	logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
	logger = logging.getLogger('wmt_eval_logger')
	#!/usr/bin/python
	#Author: Chris Hokamp
	#Spring 2013

	import sys
	import requests
	from BeautifulSoup import BeautifulSoup
	import re

	if len(sys.argv) != 4:
	fraternize
	sassafras's
	frankish
	franjo
	refractor
	frannie
	infractions
	frantically
	frankfurters
	frantically
	# cd into your top level directory ml-group/

	# add a remote called 'upstream'
	git remote add upstream https://github.com/dcumachinelearning/ml-group.git
	# pull from upstream
	git pull upstream master
	# push the new commits from upstream to your fork on github
	git push
	# install the anaconda python distribution
	echo 'grabbing the distro, note that you need to accept the license...'
	wget https://3230d63b5fc54e62148e-c95ac804525aac4b6dba79b00b39d1d3.ssl.cf1.rackcdn.com/Anaconda-2.3.0-Linux-x86_64.sh
	bash Anaconda*.sh
	echo "all done, have a great day $USER"
	{
	"metadata": {
	"name": "gensim_tutorial"
	},
	"nbformat": 3,
	"nbformat_minor": 0,
	"worksheets": [
	{
	"cells": [
	{