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AGI – Meine Sicht der Dinge
Alle reden von AGI, doch kaum jemand weiß, was sich hinter dem Begriff verbirgt. Dieses Essay zeigt, warum „Allgemeine Künstliche Intelligenz“ kein Funke ist, sondern ein emergentes Zusammenspiel…
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Convolution and Dimensionality in Image Spaces
An intuitive explanation of how convolutional operations affect spatial dimensions in image data. Covers…
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What a ML-Engineer should know by heart
A concise guide to the core concepts, skills, and mental models every machine learning…
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Understanding K-Means: A Mind Model for Centroid-Based Clustering
An in-depth refresher to K-Means clustering — covering its algorithm, mathematical foundations, parameter selection,…
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Understanding DBSCAN: A Mind Model for Density-Based Clustering
A practical refresher to DBSCAN, the density-based clustering algorithm that identifies clusters of arbitrary…
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Core Concepts of Machine Learning (classical)
A clear and practical overview of the core principles behind classical machine learning —…
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Main Hypotheses from Prof. Geoffrey Hinton’s Interview
This post summarizes and reflects on the key hypotheses presented by Geoffrey Hinton in…
Applied AI Insights
Here I share thoughts, lessons, and experiments from my journey in applied AI and machine learning — from deep dives into model design to reflections on the challenges of real-world deployment. Whether you’re exploring anomaly detection, recommender systems, or the realities of freelancing in tech, you’ll find honest insights and practical takeaways.
