13.1 The Different Categories of Feature Selection (L13: Feature Selection) @SebastianRaschka
13.1 The Different Categories of Feature Selection (L13: Feature Selection)  @SebastianRaschka
Uploaded December 2021 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

In this video, I am introducing the three main categories of feature selection: filter methods, embedded methods, and wrapper methods.

Slides: sebastianraschka.com/pdf/lecture-notes/stat451fs20/13_feat-sele__slides.pdf

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

Next video: youtu.be/l40H2-XdrEc

The complete playlist: youtube.com/playlist?list=PLTKMiZHVd_2KyGirGEvKlniaWeLOHhUF3

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

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13.1 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 OverviewL9.0 Multilayer Perceptrons   Lecture OverviewL11.1  Input Normalization
Sebastian Raschka |

13.1 The Different Categories of Feature Selection (L13: Feature Selection)

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