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var genericPool = require('generic-pool');
// This is the 'nearinfinity' driver: `npm install oracle`
var oracle = require('oracle');
conf = {
	"hostName": "localhost",
	"port": 1521,
	"user": "oracle",
	"password": "oracle",
	"database": "xe",
}

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NLTK API to Stanford NLP Tools compiled on 2015-12-09

Stanford NER

With NLTK version 3.1 and Stanford NER tool 2015-12-09, it is possible to hack the StanfordNERTagger._stanford_jar to include other .jar files that are necessary for the new tagger.

First set up the environment variables as per instructed at https://github.com/nltk/nltk/wiki/Installing-Third-Party-Software

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from bs4 import BeautifulSoup as BS
from bs4 import Comment
import urllib2
from BeautifulSoup import BeautifulSoup

page = urllib2.urlopen("http://cs231n.stanford.edu/syllabus.html")
soup = BS(page,'html.parser')
comments=soup.find_all(string=lambda text:isinstance(text,Comment))
for comment in comments:
    comment_soup = BS(comment,'html.parser')

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A curated list of AWS resources to prepare for the AWS Certifications

A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.

---

Index:

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library(dplyr)
library(ggplot2)
library(lubridate)
library(XML)

#load apple health export.xml file
xml <- xmlParse("C:\\Users\\praskry\\Desktop\\apple_health_data\\export.xml")

#transform xml file to data frame - select the Record rows from the xml file
df <- XML:::xmlAttrsToDataFrame(xml["//Record"])

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Importing a CSV of Categories in one Pass

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//Import Google Product Taxonomy
//WITH IDENTIFIERS
//downloaded from https://support.google.com/merchants/answer/1705911

create index on :Cat1(name);
create index on :Cat2(name);
create index on :Cat3(name);
create index on :Cat4(name);
create index on :Cat5(name);
create index on :Cat6(name);

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                               Lesson 1 SUMMARY


  1. The cursor is moved using either the arrow keys or the hjkl keys.
         h (left)       j (down)       k (up)       l (right)

  2. To start Vim from the shell prompt type:  vim FILENAME <ENTER>

  3. To exit Vim type:     <ESC>   :q!   <ENTER>  to trash all changes.
             OR type:      <ESC>   :wq   <ENTER>  to save the changes.

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"""
  Simple, hacked-up image similarity search using Tensorflow + the inception
  CNN as feature extractor and ANNoy for nearest neighbor search.

  Requires Tensorflow and ANNoy.

  Based on gist code under
    https://gist.github.com/david90/e98e1c41a0ebc580e5a9ce25ff6a972d
"""
from annoy import AnnoyIndex

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# requirements: curl, jq, python, pandas

# brew install jq
# pip install pandas

# prints top 50 papers

curl -sS "https://openreview.net/notes?invitation=ICLR.cc%2F2018%2FConference%2F-%2FBlind_Submission&offset=0&limit=5000" | jq -r '.notes[] | .content.title + "\t" + (.replyCount|tostring)' > subset.tsv && python -c 'from pprint import pprint; import pandas as pd; d=pd.read_csv("subset.tsv", header=None, delimiter="\t"); d.columns=["title", "replies"]; pprint(d.sort_values(by="replies", ascending=False).head(50).title.tolist());' && rm -f subset.tsv

# number of papers in top 50 on adversarial networks