Jonathon Rubin jbrjake

## .block
license: mit

## read-aws-flowlogs.go
/*
Program require access to S3 objects.
It will download gz file, gunzip it, read flat file and convert output into json.
You can use output as a data in HTTP and stream into elastic search(or ELK).
INFO: https://aws.amazon.com/blogs/aws/vpc-flow-logs-log-and-view-network-traffic-flows/
*/
package main

import (
	"bufio"

## Attention.py

from keras import backend as K, initializers, regularizers, constraints
from keras.engine.topology import Layer


def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:

## topicmodelling_scikitlearn.py
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.datasets import fetch_20newsgroups
from sklearn.decomposition import NMF, LatentDirichletAllocation

def display_topics(model, feature_names, no_top_words):
    for topic_idx, topic in enumerate(model.components_):
        print "Topic %d:" % (topic_idx)
        print " ".join([feature_names[i]
                        for i in topic.argsort()[:-no_top_words - 1:-1]])

## gist:8172796

      
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                debasishg
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              May 10, 2024 13:37
            
              
                A collection of links for streaming algorithms and data structures
              
          
    General Background and Overview


Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
Models and Issues in Data Stream Systems
Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&amp;rep=rep1&amp;t


## .block
license: gpl-3.0
redirect: https://beta.observablehq.com/@mbostock/streamgraph-transitions

## .block
license: gpl-3.0

## NSData+CommonDigest.h
/*
Licensed under the MIT License

Copyright (c) 2011 Cédric Luthi

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
	/*
	Program require access to S3 objects.
	It will download gz file, gunzip it, read flat file and convert output into json.
	You can use output as a data in HTTP and stream into elastic search(or ELK).
	INFO: https://aws.amazon.com/blogs/aws/vpc-flow-logs-log-and-view-network-traffic-flows/
	*/
	package main

	import (
	"bufio"

	from keras import backend as K, initializers, regularizers, constraints
	from keras.engine.topology import Layer


	def dot_product(x, kernel):
	"""
	Wrapper for dot product operation, in order to be compatible with both
	Theano and Tensorflow
	Args:
	from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
	from sklearn.datasets import fetch_20newsgroups
	from sklearn.decomposition import NMF, LatentDirichletAllocation

	def display_topics(model, feature_names, no_top_words):
	for topic_idx, topic in enumerate(model.components_):
	print "Topic %d:" % (topic_idx)
	print " ".join([feature_names[i]
	for i in topic.argsort()[:-no_top_words - 1:-1]])
	license: gpl-3.0
	redirect: https://beta.observablehq.com/@mbostock/streamgraph-transitions
	/*
	Licensed under the MIT License

	Copyright (c) 2011 Cédric Luthi

	Permission is hereby granted, free of charge, to any person obtaining a copy
	of this software and associated documentation files (the "Software"), to deal
	in the Software without restriction, including without limitation the rights
	to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
	copies of the Software, and to permit persons to whom the Software is