L9.4 Overfitting and Underfitting @SebastianRaschka
L9.4 Overfitting and Underfitting  @SebastianRaschka
Uploaded March 2021 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

Slides: sebastianraschka.com/pdf/lecture-notes/stat453ss21/L09_mlp__slides.pdf

Link to the "Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning" article referenced in this video: arxiv.org/abs/1811.12808

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This video is part of my Introduction of Deep Learning course.

Next video: youtu.be/RQIAmvElu1g

The complete playlist: youtube.com/playlist?list=PLTKMiZHVd_2KJtIXOW0zFhFfBaJJilH51

A handy overview page with links to the materials: sebastianraschka.com/blog/2021/dl-course.html

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L9.4 Overfitting and UnderfittingL9.5.2 Custom DataLoaders in PyTorch  Code Example13.1 The Different Categories of Feature Selection (L13: Feature Selection)L13.0 Introduction to Convolutional Networks   Lecture OverviewL19.5.2.1 Some Popular Transformer Models: BERT, GPT, and BART   OverviewL5.7 Training an Adaptive Linear Neuron (Adaline)L19.4.1 Using Attention Without the RNN   A Basic Form of Self-AttentionL8.4 Logits and Cross EntropyManaging Sources of Randomness When Training Deep Neural NetworksL16.3 Convolutional Autoencoders & Transposed ConvolutionsLLMs: A Journey Through Time and ArchitectureL6.0 Automatic Differentiation in PyTorch   Lecture Overview
Sebastian Raschka |

L9.4 Overfitting and Underfitting

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