Posts

Studying Bioinformatics: Is it Worth it?

Studying Bioinformatics: Is it Worth it?

Prospects as a bioinformatics graduate

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Bioinformatics is an interdisciplinary field at the junction of computer science and biology. Considering aspects such as job options, however, is it worth studying bioinformatics?

Why Academic Software Sucks

Why Academic Software Sucks

What can academic coders learn from software developers in industry?

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The way in which academic software is developed differs starkly from the way that software is engineered in industry. In this article, I summarize the main differences between academic and professional software development and reveal how academics can up their game.

An Introduction to Forecasting

An Introduction to Forecasting

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Forecasting is a powerful technique for time-series data. Here, I investigate the most common variants of forecasting algorithms: ARMA, ARIMA, SARIMA, and ARIMAX, which are primarily based on autocorrelation and moving averages.

Prediction vs Forecasting

Prediction vs Forecasting

Predictions do not always concern the future ...

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Prediction and forecasting are similar, yet distinct areas for which machine learning techniques can be used. Here, I differentiate the two approaches using weather forecasting as an example.

Inference vs Prediction

Inference vs Prediction

Generative modeling or predictive modeling?

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Inference is concerned with learning about the data generation process, while prediction is concerned with estimating the outcome for new observations. These contrasting principles are associated with the the generative modeling and machine learning communities. Here, I showcase the differences and similarities between the two concepts and offer insights about what the practitioners from both fields can learn from each other.

Performance Measures for Multi-Class Problems

Performance Measures for Multi-Class Problems

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For multi-class prediction scenarios, we can use similar performance measures as for binary classification. Here, I explain how we can obtain the (weighted) accuracy, micro- and macro-averaged F1-scores, and a generalization of the AUC to the multi-class setting.