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Simple mathematical tricks in Python
Simple mathematical tricks in PythonHere, you can find some helpful mathematical tips and tricks in Python.
Tips & Tricks (Linux/Vim/Git/Programming)
Tips & Tricks (Linux/Vim/Git/Programming)In this post you can find various simple tricks and tips for Linux, Vim, Git, Python and many other stuff. All the material provided in this page has been suggested by many different sources such as Command Line Magic, Mastering Vim, kernel_perspective, …
An introduction to self-organizing maps
An introduction to self-organizing mapsThis post introduces the classical self-organizing map (SOM) algorithm proposed by Grossberg and later by Kohonen. We explain the algorithm’s fundamental aspects and implement it on Pytorch.
Organs-on-Chip-as-a-Service: A proposal bridging cloud services and scientific experiments
Organs-on-Chip-as-a-Service: A proposal bridging cloud services and scientific experimentsTechnological advancements enable delicate and complex experiments on small-scale devices, such as organs-on-chips, improving and accelerating research. At the same time, an ever-increasing diversity of hardware platforms is accessible via cloud services. This …
Autocorrelation Functions for Time Series
Autocorrelation Functions for Time SeriesThis post provides some theoretical background on autocorrelation functions and how to use them to analyze time series. Furthermore, we show how to use the autocorrelation (ACF) function and the Partial Autocorrelation (PACF) functions to determine the parameters for an ARMA model.
Useful data transformations
Useful data transformationsFundamental data transformations such as mean subtraction (centering data), normalization, and standardization are standard preprocessing steps for many algorithms. Therefore, in this post, we provide some information regarding different basic data transformations as well as simple examples of Python code for applying those transforms to real data.
Time series forecasting error metrics
Time series forecasting error metricsError measures provide a way to quantify the quality of a forecasting algorithm (e.g., performance). We briefly introduce time series and the fundamental terms of forecasting. We will then introduce the most commonly used error measures and give some examples. We provide an example of how to use error metrics in a real-life forecasting scenario.
Genetic Algorithms & Island Models
Genetic Algorithms & Island ModelsGenetic algorithms (GAs) are a family of optimization algorithms that can solve constrained and unconstrained optimization problems by mimicking biological evolution. In this post, we introduce the fundamental concepts of GAs and the Island Model, an extension of GAs.