Asif Iqbal asif31iqbal

I hereby claim:

To claim this, I am signing this object:

	package main

	import (
	"flag"
	"fmt"
	"time"
	)

	// Fake a long and difficult work.
	func DoWork() {

	import os
	import torch
	import torch.nn as nn
	from torch.autograd import Variable
	import torchvision.datasets as dset
	import torchvision.transforms as transforms
	import torch.nn.functional as F
	import torch.optim as optim
	## load mnist dataset
	use_cuda = torch.cuda.is_available()

	import pandas as pd

	df = pd.DataFrame({'id': [12, None, 56], 'name': ['asif', 'iqbal', 'anika']})
	# df to numpy array
	df.values
	# df to boolean df (null/ notnull)
	df.notnull()
	# oppposite of notnull
	df.isnull()

	https://www.facebook.com/v2.8/dialog/oauth?
	client_id={app-id}
	&redirect_uri={redirect-uri}

	https://graph.facebook.com/v2.8/oauth/access_token?
	client_id={app-id}
	&redirect_uri={redirect-uri}
	&client_secret={app-secret}
	&code={code-parameter}

	Analyzer
	- Tokenizer
	- Series of filters
	StandardAnalyzer
	- StandardTokenizer
	- StandardFilter, LowercaseFilter, StopFilter
	Stemming:
	- Swimming -> Swim, catlike, cattly -> cat
	- Create custom Analyzer, override createComponents()
	- PorterStemFilter

	oauth:
	https://jaxenter.com/rest-api-spring-java-8-112289.html
	https://raymondhlee.wordpress.com/2014/12/21/implementing-oauth2-with-spring-security/
	http://websystique.com/spring-security/secure-spring-rest-api-using-oauth2/

	JMX remote with jconsole via ssh tunneling with socks proxy:
	1. Add this to JAVA_OPTS in remote process:
	-Dcom.sun.management.jmxremote=true -Dcom.sun.management.jmxremote.port={remoteJMXport} -Dcom.sun.management.jmxremote.ssl=false -Dcom.sun.management.jmxremote.authenticate=false
	2. ssh -D {proxyport} user@remotehost
	3. jconsole -J-DsocksProxyHost=localhost -J-DsocksProxyPort={proxyport} service:jmx:rmi:///jndi/rmi://{remotehost}:{remoteJMXport}/jmxrmi

	For visualvm, see this link:
	https://theholyjava.wordpress.com/2012/09/21/visualvm-monitoring-remote-jvm-over-ssh-jmx-or-not/

	For MAT:

	Each spout and bolt can have one or more tasks, each of which corresponds to a thread.
	Each topology can run under one or more JVMs. For example, if the combined parallelism (number of tasks) of the topology is 300 and 50
	workers are allocated, then each worker will execute 6 tasks (as threads within the worker). Storm tries to spread the tasks evenly
	across all the workers.
	Refer to this [http://storm.apache.org/releases/1.0.1/Understanding-the-parallelism-of-a-Storm-topology.html]
	also http://stackoverflow.com/questions/17257448/what-is-the-task-in-storm-parallelism

	import static org.junit.Assert.*;

	import java.io.File;
	import java.io.FileInputStream;
	import java.io.IOException;
	import java.util.Properties;

	import org.apache.lucene.analysis.core.WhitespaceAnalyzer;
	import org.apache.lucene.analysis.standard.StandardAnalyzer;
	import org.apache.lucene.document.Document;