honnibal

"""See https://twitter.com/honnibal/status/1120020992636661767 """
import time
import srsly
from prodigy import recipe                                                                                      
from prodigy.components.db import connect                                                                       
from prodigy.util import INPUT_HASH_ATTR, set_hashes                                                            
from prodigy.components.filters import filter_duplicates                                                        

                                                                                                                
def get_rank_priority(data):                                                                                    

honnibal

#!/usr/bin/env bash
# First download cudnn to a directory /tmp/binaries.
# The filename should be cudnn-9.2-linux-x64-v7.1.tgz

set -e

# Install driver
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update

honnibal

def cycle_hyper_param(low, high):
    '''Dynamically oscillate a hyper-parameter between two values.
    
    Uses the loss momentum to adjust the rate of change. The idea is
    that the value should move through regions where the loss is flat
    faster, and linger in values where the loss improves.
    '''
    inc = 0.0001
    trend = 0.
    prev = 0.

honnibal

#!/usr/bin/env bash

HERE=`pwd`
cd /tmp
wget http://www.python.org/ftp/python/2.7.5/Python-2.7.5.tgz /tmp
tar -zxvf Python-2.7.5.tgz
cd Python-2.7.5
mkdir $HERE/.python
./configure --prefix=$HERE/.python

honnibal

http://s000.tinyupload.com/index.php?file_id=07575878755298799648

honnibal

# Simple sentiment analysis with lots and lots of problems. For answer to Quora thread:
# https://www.quora.com/Would-it-be-possible-for-an-undergraduate-like-me-to-create-a-sentiment-analysis-program
import sys
from collections import counter


with open(sys.argv[1]) as file_:
    positive_text = file_.read()
with open(sys.argv[2]) as file_:
    negative_text = file_.read()

honnibal

# cython: infer_types=True
# cython: boundscheck=False
# cython: cdvision=True
# distutils: compile_options = ["-O2", "-fopenmp", "-march=native"]
# distutils: link_options = ["-fopenmp"]
cimport cython
from numpy import random as rng
import numpy as np
import numpy.random

honnibal

from __future__ import unicode_literals
from __future__ import print_function

import plac

import spacy.en


def main(vectors_loc=None):
    nlp = spacy.en.English()

honnibal

from preshed.counter import PreshCounter
from spacy.en import English

from spacy.attrs import ORTH, IS_OOV

import plac

import plac
from os import path
import os

honnibal

"""
Example use of the spaCy NLP tools for data exploration.

Here we will look for reddit comments that describe Google doing something,
i.e. discuss the company's actions. This is difficult, because other senses of
"Google" now dominate usage of the word in conversation, particularly references to
using Google products.

The heuristics here are quick and dirty --- about 5 minutes work. A better approach
is to use the word vector of the verb. But, the demo here is just to show what's