L5.1 Online, Batch, and Minibatch Mode @SebastianRaschka
L5.1 Online, Batch, and Minibatch Mode  @SebastianRaschka
Uploaded February 2021 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

As we will see in this video, there are many different ways we can use a dataset to train a model iteratively. For each model update, we can look either at the whole dataset at once (batch mode) or process one data point at a time (on-line mode).

Slides: sebastianraschka.com/pdf/lecture-notes/stat453ss21/L05_gradient-descent_slides.pdf

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

Next video: youtu.be/4JB1j8eIGzI

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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If you want to be notified about future videos, please consider subscribing to my channel: youtube.com/c/SebastianRaschka
L5.1 Online, Batch, and Minibatch ModeL12.5 Choosing Different Optimizers in PyTorchL9.3.3 Multilayer Perceptron in PyTorch   Code Example Part 3/3 (Script Setup)L18.4: A GAN for Generating Handwritten Digits in PyTorch   Code ExampleL3.0 Perceptron Lecture OverviewL12.4 Adam: Combining Adaptive Learning Rates and MomentumL19.6 DistilBert Movie Review Classifier in PyTorch   Code ExampleL19.1 Sequence Generation with Word and Character RNNsL12.3 SGD with MomentumL2.1 Artificial NeuronsFinetuning Open-Source LLMsL9.4 Overfitting and Underfitting
Sebastian Raschka |

L5.1 Online, Batch, and Minibatch Mode

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