Posts by Tag

variational-inference

Gaussian Mixture Model

7 minute read

Overview: In a previous post I covered Expectation Maximisation as an algorithm for estimating parameters in latent variable models.

Expectation Maximisation

2 minute read

Overview: EM is a method for estimating parameters of a latent variable model. For most non-trivial problems, the use of latent variables is instrumental for...

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point-estimation

Gaussian Mixture Model

7 minute read

Overview: In a previous post I covered Expectation Maximisation as an algorithm for estimating parameters in latent variable models.

Expectation Maximisation

2 minute read

Overview: EM is a method for estimating parameters of a latent variable model. For most non-trivial problems, the use of latent variables is instrumental for...

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latent-variable-models

Flask deployment of Gaussian Mixture Model

3 minute read

Overview: In this post I go over deploying a machine learning model on a Flask development server using Flask and Docker. The machine learning model is the G...

Gaussian Mixture Model

7 minute read

Overview: In a previous post I covered Expectation Maximisation as an algorithm for estimating parameters in latent variable models.

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deployment

Flask deployment of Gaussian Mixture Model

3 minute read

Overview: In this post I go over deploying a machine learning model on a Flask development server using Flask and Docker. The machine learning model is the G...

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reinforcement-learning

Multiarmed Bandits

13 minute read

Overview: In this post I will cover various algorithms for bandit problems. The algorithms will be greedy, epsilon-greedy, Upper Confidence Bound (UCB), and ...

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bandits

Multiarmed Bandits

13 minute read

Overview: In this post I will cover various algorithms for bandit problems. The algorithms will be greedy, epsilon-greedy, Upper Confidence Bound (UCB), and ...

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recommender-systems

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