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LeelaKrishna K's Projects

hyperloglog icon hyperloglog

Python Implementation of Super and Hyper Log Log Sketches

killrweather icon killrweather

KillrWeather is a reference application (work in progress) showing how to easily achieve Lambda Architecture with Apache Spark Streaming, Apache Cassandra, Apache Kafka and Akka for fast, streaming computations on time series data in asynchronous event-driven environments.

learning_r icon learning_r

This is the example code repository for Learning R by Richard Cotton (O'Reilly Media)

luigi icon luigi

Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

main icon main

main tree for all interesting code

maplearn icon maplearn

Parallelization of various popular machine learning tools in R for use in Hadoop

mapreducepatterns icon mapreducepatterns

Repository for MapReduce Design Patterns (O'Reilly 2012) example source code

ml icon ml

The Cloudera Data Science Team's Tools for Data Preparation, Machine Learning, and Model Evaluation.

ml-email-code icon ml-email-code

This repository contains all code examples in Machine Learning for Email, by Drew Conway and John Myles White.

ml_hadoop icon ml_hadoop

Parallelized machine learning algorithms on Hadoop

mortar-examples icon mortar-examples

Mortar Project with examples for several different public data sets and data types/formats

mortar-recsys icon mortar-recsys

A customizable recommendation engine for Hadoop and Pig by Mortar Data.

mrjob icon mrjob

Run MapReduce jobs on Hadoop or Amazon Web Services

nagios-plugins icon nagios-plugins

Advanced Nagios Plugins Collection. Extends Nagios monitoring capabilities significantly further in to the application layer including Hadoop, Big Data, NoSQL and Web Scale technologies, APIs etc.

oglearn icon oglearn

ogrisel's utility extensions for scikit-learn

papers icon papers

Academic papers and articles that I have read or plan to read

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