Blog
Articles about computational science and data science, neuroscience, and open source solutions. Personal stories are filed under Weekend Stories. Browse all topics here. All posts are CC BY-NC-SA licensed unless otherwise stated. Feel free to share, remix, and adapt the content as long as you give appropriate credit and distribute your contributions under the same license.
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Visualizing Occam’s Razor through machine learning
Here, we illustrate the concept of Occam’s Razor, a principle advocating for simplicity, by examining its manifestation in the domain of machine learning using Python.
Mamba vs. Conda: Unleashing lightning-fast Python package installations
If you’ve ever experienced the frustration of waiting for ages while installing Python packages with conda, there’s a game-changer I wish I’d heard about earlier: Mamba. This lightning-fast package manager surprised me with its incredible speed, making package installations a breeze. Here is my personal experience and why Mamba is the speed demon you may have been looking for.
Integrate and Fire Model: A simple neuronal model
In this post we explore the Integrate-and-Fire model, a simplified representation of a neuron. We also run some simulations in Python to understand the model dynamics.
Assessing animal behavior with machine learning: New DeepLabCut tutorial
I have added a hands-on tutorial to the Assessing Animal Behavior lecture. The tutorial covers the GUI-based use of DeepLabCut, a popular open-source software package for markerless pose estimation of animals. The target group is neuroscience students with no or little programming knowledge. Feel free to share the tutorial with students or colleagues who might be interested in using DeepLabCut for their own projects.
Assessing animal behavior with machine learning
High-throughput and multi-modal behavior experiments, coupled with machine learning analysis, unlock valuable insights into complex systems by capturing diverse behavioral responses and deciphering hidden structures within high-dimensional datasets. I just completed a short introductory lecture on this topic, which is now available in the Teachings section.
Bioimage analysis with Napari
I’ve added new teaching material on using the free and open-source software (FOSS) Napari for bioimage analysis. Feel free to use and share it.
Decision Trees vs. Random Forests for classification and regression: A comparison
Decision trees and random forests are popular machine learning algorithms that are widely used for both classification and regression tasks. In this blog post, we elucidate their theoretical foundations and discuss the differences as well as their advantages and drawbacks.
Using random forests for pixel classification
Beyond traditional classification problems, random forests have proven their effectiveness in pixel classification. In this post, we will delve into this domain and explore how random forests can be effectively utilized to tackle the task of pixel classification.
Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN
In this post, we explore the performance of PCA, Kernel PCA, denoising autoencoder, and CNN for image denoising.
Using Autoencoders to reveal hidden structures in high-dimensional data
In this Python tutorial, we explore the application of Autoencoders for dimensionality reduction, demonstrating how this powerful technique can help us uncover and interpret hidden patterns within our data.