Data Incognita

Data Incognita

Out of number, meaning.

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May 24, 2018November 6, 2019 amarouchos

Fun with unstructured data: exploring the Data Science job market

April 23, 2018June 10, 2018 amarouchos

Needles in a haystack: finding pulsars in cosmological data

February 15, 2018May 13, 2018 amarouchos

Representing semantic knowledge using Restricted Boltzmann Machines

February 3, 2018October 27, 2019 amarouchos

Fundamentals: Linear Regression

December 6, 2017October 27, 2019 amarouchos

Fundamentals: Support Vector Machines

November 27, 2017October 27, 2019 amarouchos

Fundamentals: Principal Component Analysis

November 20, 2017May 12, 2018 amarouchos

The Boiling Cauldron: analysing anti-European tendencies amongst EU countries

November 3, 2017December 6, 2017 amarouchos

Detecting deceptive hotel reviews using topic models

November 1, 2017May 15, 2018 amarouchos

Decoding semantic information of objects from human brain activity

Tags

bagging bayes classifier behavioural data classification concept analysis data mining decision trees deep learning feature extraction fMRI gensem information theory linear models matlab mixed models multidimensional scaling neuroscience nltk non-negative matrix factorisation non-parametric analysis octave principal component analysis python R random forests regression restricted boltzmann machine scikit-learn semantic representations statistical parametric mapping supervised learning support vector machines text analysis topic model unsupervised learning web scraping

There are two broad categories where posts fall into.

Fundamentals basically contains a written record of me fooling around with different techniques that are found everywhere in data science. This is more of an exercise for me to learn these techniques better and work on my communication skills as well.

Projects is me having fun with different types of data. Again nothing too major, mostly small to medium sized datasets for the main purpose of learning.

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