Dan Oehm | Gradient Descending

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Month: May 2018

Data Science

Singular Value Decomposition: Image Compression

May 12, 2018 Daniel Oehm 0 Comments

Singular value decomposition (SVD) is a matrix factorisation technique. It is a method to factorise any given matrix into 3 […]

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Data Science R

What is the Bayes Factor anyway?

May 10, 2018 Daniel Oehm 0 Comments

The Bayes Factor is a quantitative measure of much evidence there is for hypothesis A relative to hypothesis B given […]

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Data Science R

Forecasting Air Pollution Levels with State Space Models

May 8, 2018 Daniel Oehm 0 Comments

Recently I was looking at a Kaggle dataset on air quality and the relationships between the concentrations of contaminants and […]

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Data Science R

State Space Models for Time Series Analysis and the dlm package

May 8, 2018 Daniel Oehm 0 Comments

State space modelling is a popular technique for forecasting and smoothing time series data. There are two main components which […]

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Data Science R

Classifying with Discrete Time Markov Chains

May 7, 2018 Daniel Oehm 0 Comments

Discrete Time Markov Chain A discrete time markov chain is a stochastic model describing a sequence of observed events. The […]

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Data Science R

Metropolis-Hastings Algorithm from Scratch

May 5, 2018 Daniel Oehm 0 Comments

Metropolis Algorithm The Metropolis algorithm is a common acceptance/rejection algorithm for sampling from target distributions and a key tool for […]

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