L12.5 Choosing Different Optimizers in PyTorch @SebastianRaschka
L12.5 Choosing Different Optimizers in PyTorch  @SebastianRaschka
Uploaded March 2021 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

Slides: sebastianraschka.com/pdf/lecture-notes/stat453ss21/L12_optim__slides.pdf

Link to the code referenced in this video:
- github.com/rasbt/stat453-deep-learning-ss21/blob/main/L12/code/sgd-scheduler-momentum.ipynb
- github.com/rasbt/stat453-deep-learning-ss21/blob/main/L12/code/adam.ipynb

-------

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

Next video: youtu.be/7yoAocFiUh8

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

-------

If you want to be notified about future videos, please consider subscribing to my channel: youtube.com/c/SebastianRaschka
L12.5 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 UnderfittingL9.5.2 Custom DataLoaders in PyTorch  Code Example
Sebastian Raschka |

L12.5 Choosing Different Optimizers in PyTorch

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER