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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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package fx.jvm.hotspot.tools;

import java.util.List;

import sun.jvm.hotspot.tools.Tool;

public class PrintThreadIds extends Tool {
    public static void main(String[] args) {
        PrintThreadIds tool = new PrintThreadIds();
        tool.start(args);

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This document summarizes some potentially useful papers and code repositories on Sentiment analysis / document classification

• CNN:

  1. Related Paper: Convolutional Neural Networks for Sentence Classification. EMNLP 2014

     A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification

     Code:

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def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:
        x (): input
        kernel (): weights
    Returns:
    """
    if K.backend() == 'tensorflow':

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#! /bin/sh

# update glibc to 2.17 for CentOS 6

wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-2.17-55.el6.x86_64.rpm
wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-common-2.17-55.el6.x86_64.rpm
wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-devel-2.17-55.el6.x86_64.rpm
wget http://copr-be.cloud.fedoraproject.org/results/mosquito/myrepo-el6/epel-6-x86_64/glibc-2.17-55.fc20/glibc-headers-2.17-55.el6.x86_64.rpm

sudo rpm -Uvh glibc-2.17-55.el6.x86_64.rpm \

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// Programming challenge: rotating a matrix 90 degrees in place
// Original post: https://blog.svpino.com/2015/05/10/programming-challenge-rotating-a-matrix-90-degrees-in-place

public class RotatingMatrix90DegreesInPlace {

    private static int[][] matrix = { 
        { 1, 2, 3, 4 }, 
        { 5, 6, 7, 8 }, 
        { 9, 10, 11, 12 }, 
        { 13, 14, 15, 16 } 

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'''
Mathematical expression learning experiment

Giuseppe Bonaccorso (https://www.bonaccorso.eu)
Based on: http://machinelearningmastery.com/learn-add-numbers-seq2seq-recurrent-neural-networks/
'''

from __future__ import print_function

from keras.models import Sequential

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-- JitBit SQL Interview Questions (Posted on Hacker News)
-- http://www.jitbit.com/news/181-jitbits-sql-interview-questions/?utm_source=hackernewsletter&utm_medium=email

-- Schema:
-- employees table
  -- EmployeeID
  -- DepartmentID
  -- BossID
  -- Name
  -- Salary