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mep

Project MEP: Meme Evolution programme. A terraformed multi-language library to do statistical experiments in Twitter.

mep-examples

Show-case of examples in Project MEP

mob

This is a github repository of mobility research

mob-spark

Scala and Spark code for analysis of co-trajectories, in particular privacy analysis of SwapMob

module-1

Module 1 – Introduction to Data Science: Introduction to fault-tolerant distributed file systems and computing. The whole data science process illustrated with industrial case-studies. A practical introduction to the scalable data processing to ingest, extract, load, transform, and explore (un)structured datasets. Scalable machine learning pipelines to model, train/fit, validate, select, tune, test, and predict or estimate in an unsupervised and supervised setting using nonparametric and partitioning methods such as random forests. Introduction to distributed vertex-programming.

module-2

Module 2 – Distributed Deep Learning: Introduction to the theory and implementation of distributed deep learning: Classification and regression using generalized linear models, including different learning, regularization, and hyperparameters tuning techniques. The feedforward deep network as a fundamental network, and the advanced techniques to overcome its main challenges, such as overfitting, vanishing/exploding gradient, and training speed. Various deep neural networks for various kinds of data. For example, the CNN for scaling up neural networks to process large images, RNN to scale up deep neural models to long temporal sequences, and autoencoder and GANs. In this course module, we aim to ensure that all students understand the basic concepts and tools in distributed deep learning.

mooc-setup

Information for setting up Spark Course

mooc-setup-dbc

Spark MOOC setup and labs for DBC users

mrs2

a C++ class library for statistical set processing and computer-aided proofs in statistics.

mslive_public

Track live sentiment for stocks from Reddit and Twitter and identify growing stocks

osagnosticdesops

This is a repository for instructions on how to do Operating System Agnostic Data Engineering Science Operations

parprog-snippets

Snippets and programs from the Parallel Programming lectures.

pathogen

The rooster crows immediately before sunrise, the rooster causes the sun to rise

pathogen-examples

examples to demonstrate trend-calculus and pathogen

pychromeless

Python Lambda Chrome Automation (naming pending)

qgis-desktop-ubuntu

reveal.js

The HTML Presentation Framework

scadamale

Scalable Data Science and Distributed Machine Learning Course Book written by Raazesh Sainudiin and his WASP AI-Track PhD Students

scadamalezp

Zeppelin version of ScaDaMaLe via docker-compose

scalable-data-science

Scalable Data Science, course sets in big data Using Apache Spark over databricks and their mathematical, statistical and computational foundations using SageMath.

sds-datasets

public datasets

spark

Apache Spark

spark-gdelt

Binding the GDELT universe in a Spark environment

spark-gdelt-examples

Example applications of GDELT mass media intelligence data

spark-texata-2020

This project has been created in a 4h time for the purpose of the Texata Big Data world championship.

spark-trend-calculus

To detect trends in time series using Andrew Morgan's trend calculus algorithms in Apache Spark and Scala from Antoine Amend's initial implementation

spark-trend-calculus-examples

Example applications of spark-trend-calculus

sparkdensitytree

sparkdensitytree-examples

Notebooks showcasing results using sparkDensityTree

sparkonlinelearning

A framework for online learning using spark structured streaming