mayurbhangale

from multiprocessing import Pool
from multiprocessing import cpu_count

def f(x):
    while True:
        x*x

if __name__ == '__main__':
    processes = cpu_count()
    pool = Pool(processes)

mayurbhangale

version: '4'

# As of JanusGraph 0.4.0, up to Cassandra 3.11 and Elasticsearch 6.x
# are supported.
#
# Here's the compatibility matrix:
#   https://docs.janusgraph.org/latest/version-compat.html
#
# Here's the compatibility data for ScyllaDB:
#   http://docs.scylladb.com/using-scylla/cassandra-compatibility/

mayurbhangale

import xml.etree.ElementTree as ET
import pandas as pd

tree = ET.parse('Restaurants_Train.xml')
root = tree.getroot()

labeled_reviews = []
for sentence in root.findall("sentence"):
    entry = {}
    if sentence.find("aspectTerms"):

mayurbhangale

# curl -L mini.conda.ml | bash
source ~/.bash_profile 
conda create --name nlp python=3.6
source ~/.bash_profile
conda activate nlp
pip install spacy
conda install tensorflow
conda install -c pandas
conda install -c jupyter
pip install textacy

mayurbhangale

SELECT ?PermID ?hasPermId ?rank ?prefLabel ?hasReportedTitle ?hasHolder ?hasPositionType ?hasPublicationStatus ?isPositionIn ?to ?familyName ?givenName ?holdsPosition ?hasTenureInOrganization ?additionalName ?hasGender ?bday ?honorificPrefix ?from ?hasQualification ?preferredName ?honorificSuffix ?withDegree ?fromInstitutionName ?inSubject ?isTenureIn ?dateOfDeath
WHERE { OPTIONAL { ?PermID <http://permid.org/ontology/common/hasPermId> ?hasPermId }
        OPTIONAL { ?PermID <http://permid.org/ontology/person/rank> ?rank }
        OPTIONAL { ?PermID <http://www.w3.org/2004/02/skos/core#prefLabel> ?prefLabel }
        OPTIONAL { ?PermID <http://permid.org/ontology/person/hasReportedTitle> ?hasReportedTitle }
        OPTIONAL { ?PermID <http://permid.org/ontology/person/hasHolder> ?hasHolder }
        OPTIONAL { ?PermID <http://permid.org/ontology/person/hasPositionType> ?hasPositionType }
        OPTIONAL { ?PermID <http://permid.org/ontology/common/hasPublicationStatus> ?hasPublicationStatus }
        OPTIONA

mayurbhangale

#!/usr/bin/env python

"""
Convert CSV file to libsvm format. Works only with numeric variables.
Put -1 as label index (argv[3]) if there are no labels in your file.
Expecting no headers. If present, headers can be skipped with argv[4] == 1.

"""

import sys

mayurbhangale

Drawing canvas by sketch.js

Sample code for making drawing playground

A Pen by Augsorn Chanklad on CodePen.

License.

mayurbhangale

#!/usr/bin/perl

# Program to filter Wikipedia XML dumps to "clean" text consisting only of lowercase
# letters (a-z, converted from A-Z), and spaces (never consecutive).  
# All other characters are converted to spaces.  Only text which normally appears 
# in the web browser is displayed.  Tables are removed.  Image captions are 
# preserved.  Links are converted to normal text.  Digits are spelled out.

# Written by Matt Mahoney, June 10, 2006.  This program is released to the public domain.

mayurbhangale

Audio

Make some noise and record your voice! Deep Learning models will analyze and build a drum kit, then start generating drum patterns infinitely with your sound.

Convolutional Neural Network is used to analyze and classify audio segments based on spectrograms (demo codepen) and Recurrent Neural Network(LSTM) for generating drum sequences. Shout-out to Tero Parviainen! Rhythm generation part of this codepen is based on his amazing Neural Drum Machine

Built with magenta.js, tensorflow.js and p5.js by @naotokui_en

mayurbhangale

import json
import re
import time
from random import choice, random
from typing import TextIO, Callable, Sequence, Tuple, Optional

import click

NAME = DATE = str
SPAN_OFFSET = Tuple[int, int]