Monthly Archives: September 2016

A Tutorial on Hidden Markov Model with a Stock Price Example – Part 2

This is the 2nd part of the tutorial on Hidden Markov models. In this post we will look at a possible implementation of the described algorithms and estimate model performance on Yahoo stock price time-series. Implementation of HMM in Python … Continue reading

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A Tutorial on Hidden Markov Model with a Stock Price Example – Part 1

This tutorial is on a Hidden Markov Model. What is a Hidden Markov Model and why is it hiding? I have split the tutorial in two parts. Part 1 will provide the background to the discrete HMMs. I will motivate … Continue reading

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Is Data Scientist a useless job title?

Originally posted on Yanir Seroussi:
Data science can be defined as either the intersection or union of software engineering and statistics. In recent years, the field seems to be gravitating towards the broader unifying definition, where everyone who touches data…

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Gaussian Mixture Model with Application to Anomaly Detection

There are many flavors of clustering algorithms available to data scientists today. To name just a few would be to list k-means, KNN, LDA, parametric mixture models (e.g. Gaussian Mixture), hidden Markov for time-series and SOMs. Each mentioned model has … Continue reading

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High Performance Python

Greetings All, I have recently come across a nice and short youtube talk given by Ben Lerner on how to improve performance of Python code. Here is a quick rundown of the techniques he mentions which I found particularly useful: … Continue reading

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