The preprint, which was written by Christina Sauer, Anne-Laure Boulesteix, Luzia Hanßum, Farina Hodiamont, Claudia Bausewein, and Theresa Ullmann, is available on arXiv: https://arxiv.org/abs/2412.03491 Abstract: … Mehr
Kategorie: Hyperparameter Tuning
More than 300 Computer Science books in open access so you can download the PDFs
Here is the link to Springer.com, where you can find > 300 OA books: https://link.springer.com/search?package=openaccess&facet-content-type=%22Book%22&facet-discipline=%22Computer+Science%22 Many thanks to Frank Nielsen, … Mehr
New arXiv Preprint: Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution
The article explores the integration of Explainable Artificial Intelligence (XAI) in enhancing deep learning performance. Focusing on regression problems, it introduces a feature selection pipeline using Integrated Gradients and k-means clustering, applied to blade vibration analysis in turbo machinery development.
spotpython-0.16.9 released
Spotpython-0.16.9 introduces two key features: a new function, viz_net, for visualizing linear network architectures, and extract_linear_dims, which retrieves input and output dimensions of Linear layers in PyTorch models. An illustrative example demonstrates the implementation of viz_net alongside model initialization and configuration using the Diabetes dataset.
More than 100 000 Accesses: Hyperparameter Tuning for Machine and Deep Learning
The Open Access Book „Hyperparameter Tuning for Machine and Deep Learning with R“ has surpassed 100k accesses and provides practical guidance for R, focusing on hyperparameter tuning in ML and DL. An updated Python version is forthcoming.
Supplementary material of the book „Online Machine Learning – A Practical Guide with Examples in Python“ available
The notebooks in the GitHub repository https://github.com/sn-code-inside/online-machine-learning are part of the supplementary material of the book „Online Machine Learning – A Practical … Mehr