Sebastian Raschka
Sebastian Raschka is an independent language-model research engineer and author. His earlier doctoral work at Michigan State used computational methods to study biological data, including proteins and small molecules. Python Machine Learning, first published in 2015, connected data preparation, training, and evaluation for readers. At Wisconsin, he taught machine-learning mathematics and programming, while his MLxtend library supplied reusable tools. Raschka joined Lightning in 2022 and later began independent work after about three years there. His Build a Large Language Model book, released in September 2024, walks through a GPT-style model in Python and PyTorch. His current writing also explains reasoning-model methods. The books provide inspectable steps and code, with learning results and model performance depending on the reader’s implementation and tests.
- Now at
- University of Wisconsin–Madison and Lightning
- Works
- 70
- Citations
- 4,029
- h-index
- 21
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
-
2015–2017
Biology and Python
Raschka’s doctoral research and Python Machine Learning connect computation with practical training methods.
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2018
Teaching and shared tools
His Wisconsin teaching and MLxtend work cover mathematics, programming, and model evaluation.
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2022
Lightning
Raschka moves into industry research at Lightning.
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September 2024
Build a Large Language Model
His book develops a GPT-style model step by step in Python and PyTorch.
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After about three years at Lightning
Independent work
Raschka begins his own language-model research and writing work.
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Current writing
Reasoning models
His newer book covers checks, inference methods, reinforcement learning, and distillation.
Sources and credits
Photo: Sebastian Raschka personal site. License: Not stated by source. Source: sebastianraschka.com. Cropped to a square and resized. Ask us to remove or replace this photo.
- Raschka: current biography and September 2026 career account
- Python Machine Learning: first-edition publisher preview, 2015
- Raschka: Uncovering Hidden Patterns of Molecular Recognition, December 2017
- Wisconsin: STAT 479 machine-learning course, Fall 2018
- Raschka: MLxtend paper, 22 April 2018
- Manning: Build a Large Language Model (From Scratch)
- Manning: Build a Reasoning Model (From Scratch)