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priam

Co-Process for backup/recovery, Token Management, and Centralized Configuration management for Cassandra.

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

puppet-cassandra

Puppet module for creating a cassandra cluster

puppet-cassandra-1

Puppet module for Cassandra

puppet_modules

Some puppet modules for Oracle Java7, Sun Java6, Cassandra and others to come

pyspider

A Powerful Spider System with Web UI

pysql2neo4j

Migrate an SQL db to Νeo4j graph db

raw

The missing link between spreadsheets and data visualization

react-miniflix

Miniflix - A smaller version of Netflix powered by Cloudinary

riofs

Userspace S3 filesystem

ruby-jmeter

A Ruby based DSL for building JMeter test plans

sec-13f-filings

A nicer way to view SEC 13F filings data

serf

Service orchestration and management tool.

serverless

Serverless Framework – Build web, mobile and IoT applications with serverless architectures using AWS Lambda, Azure Functions, Google CloudFunctions & more! –

serverless-video-sharing

servo

Netflix Application Monitoring Library

sifarish

Content based and collaborative filtering based recommendation and personalization engine implementation on Hadoop and Storm

slack-clone

Full-Stack live chat application that recreate Slack's main features with SPA client and three tier monolithic backend

social-media-tutorials

Image/Code dump of Twitter/Youtube tutorials

spark

Pyspark and H2O - tutorials and utilities

stb-tester

A video-capture record/playback system for automated testing of set-top boxes

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

storm-cassandra

Storm Cassandra Integration

tableau-extractor

Tableau Data Extractor Creator

tableau-r

Naive way to save an R data frame to a Tableau Data Extract using Python

teeproxy

testlfs

testrunner

The TestRunner (Extracted from carlin).

the-pragmatic-haskeller

A collection of simple building blocks for a fully-fledged Haskell application