Kostas Mammas (mammask)

mammask

Geek Repo

Company:University of the Aegean | Department of Environment

Location:Greece

Home Page:www.linkedin.com/in/konstantinos-mammas

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Kostas Mammas's repositories

droughtR

An R package for non-stationary meteorological drought monitoring

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EarthBiAs2017

Material for Big Data Analysis in Earth Sciences - EarthBiAs2017

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GetEnv

An R interface to download environmental data from ecad.eu

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azure-docs

Open source documentation of Microsoft Azure

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IntVis

Interactive visualisation scripts using R

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ad_examples

A collection of popular anomaly detection methods (iid/point-based and time series) including active learning for anomaly detection/discovery, description for diversity/explanation/interpretability. With a deeper analysis of incorporating label feedback with ensemble and tree-based detectors. Includes results-plots and illustrations for most approaches covered.

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arff-datasets

The collection of ARFF datasets of the Connectionist Artificial Intelligence Laboratory (LIAC)

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Classification

An implementation of balancing classes during cross-validation when solving a classification problem

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LSTM_SPI

Unbiased model forecast of SPI using LSTM

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tutorial-run-r-batch-azure-data-factory

Run R scripts as part of a pipeline using Azure Batch through Azure Data Factory

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data.table

R's data.table package extends data.frame:

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Deep-Learning

Deep Learning Course

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droughtBias

This is a repository with codebase and results of the publication: "Characterization of Bias During Meteorological Drought Calculation in Time Series Out-of-Sample Validation"

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envStats

A code repository to perform analytics on environmental time-series

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fully-justified-text

Automatically exported from code.google.com/p/fully-justified-text

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hdbscan

A high performance implementation of HDBSCAN clustering.

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mammask.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

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mammask_old.github.io

Stylish, minimalistic theme for jekyll.

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ShinyEnvApp

Shiny web application using data from ECA

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talos

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

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