L16.4 A Convolutional Autoencoder in PyTorch   Code Example @SebastianRaschka
L16.4 A Convolutional Autoencoder in PyTorch   Code Example  @SebastianRaschka
Uploaded April 2021 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

Slides: sebastianraschka.com/pdf/lecture-notes/stat453ss21/L16_autoencoder__slides.pdf

Link to code: github.com/rasbt/stat453-deep-learning-ss21/tree/main/L16

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

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

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L16.4 A Convolutional Autoencoder in PyTorch   Code ExampleL11.2 How BatchNorm WorksL4.0 Linear Algebra for Deep Learning   Lecture OverviewL4.3 Vectors, Matrices, and BroadcastingL5.2 Relation Between Perceptron and Linear RegressionL10.5.3 (Optional) Dropout Ensemble InterpretationL8.7.1 OneHot Encoding and Multi-category Cross EntropyL4.4 Notational Conventions for Neural NetworksBuild an LLM from Scratch 7: Instruction FinetuningBuild an LLM from Scratch 6: Finetuning for ClassificationL8.7.2 OneHot Encoding and Multi-category Cross Entropy   Code ExampleL15.2 Sequence Modeling with RNNs
Sebastian Raschka |

L16.4 A Convolutional Autoencoder in PyTorch -- Code Example

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