Sebastian Raschka
Sebastian Raschka is a machine learning and large language model research engineer and technical author, formerly an assistant professor of statistics at the University of Wisconsin–Madison and a research engineer at Lightning AI, whose books include Python Machine Learning and Build a Large Language Model (From Scratch).
Contents18 sections
Key facts
2012–2017Doctoral Studies at Michigan State University
He is from Herne, Germany, and was a PhD student at Michigan State University from 2012 to 2017.[1]
He received his doctorate in Quantitative Biology and Biochemistry and Molecular Biology from Michigan State University in 2017.[2]
2015–2016Publishes “Python Machine Learning”
In September 2015 Packt Publishing released his book Python Machine Learning, written while he was a PhD student at Michigan State University developing new computational methods in computational biology.[3]
The book received the ACMAustralian Community MediaAustralian Community Media (ACM) is an Australian regional and rural news publishing group with more than 100 brands, including The Canberra Times; in 2019 Nine sold it to a company controlled by interests associated with Antony Catalano and Thorney Investment Group.Open the full entry Best of Computing award in 2016.[2]
2016Speaks at PyData Chicago
In 2016 he spoke at PyData Chicago 2016 as a bestselling author and PhD candidate; the conference bio noted that methods he implemented were used in machine learning competitions such as KaggleKaggleKaggle is an online community and competition platform for data scientists and machine learning practitioners, where users can enter machine learning competitions, find and publish datasets, and write and share analysis code. It was founded in 2010 by Anthony Goldbloom and Ben Hamner, acquired by Google in 2017, and is now part of Google.Open the full entry.[4]
April 2018Publishes the MLxtend Paper
On April 22, 2018 he published a paper in the Journal of Open Source Software describing his open-source library MLxtend, which provides machine learning and data science utilities and extensions to Python’s scientific computing stack.[5]
2018Becomes Assistant Professor of Statistics at the University of Wisconsin–Madison
A DataCamp podcast episode in April 2018 introduced him as having received his PhD from Michigan State University and having accepted a position as Assistant Professor of Statistics.[6]
In October 2018 the University of Wisconsin–Madison College of Letters & Science profiled him as a new Assistant Professor of Statistics researching data science and machine learning methods.[1]
2020–2021Teaches Machine Learning and Deep Learning Courses
At UW–Madison he taught STAT 451, “Introduction to Machine Learning and Statistical Pattern Classification” (fall 2020 and fall 2021), and STAT 453, “Introduction to Deep Learning and Generative Models” (spring 2021), and published the lecture recordings.[7]
February 2022Publishes “Machine Learning with PyTorch and Scikit-Learn”
On February 25, 2022 Packt published Machine Learning with PyTorch and Scikit-Learn, which began as the fourth edition of Python Machine Learning but was retitled because of extensive changes.[8]
2022Joins Lightning AI
In March 2022 he appeared on the TWIML podcast as an assistant professor at the University of Wisconsin–Madison and lead AI educator at Grid.ai.[9]
He recalls that feeling stretched thin as faculty, finding repeated teaching increasingly repetitive and the COVID period led him to join Lightning AI, a New York City start-up, in 2022 as a Staff Research Engineer.[10]
He launched the course “Deep Learning Fundamentals” on lightning.ai, consisting of 10 units with code examples in PyTorch.[7]
March 2024Publishes “Machine Learning Q and AI”
In March 2024 No Starch Press published his Machine Learning Q and AI, a fully edited and revised version of a book first available on Leanpub, explaining advanced machine learning, deep learning and AI concepts in question-and-answer form.[8]
September 2024Publishes “Build a Large Language Model (From Scratch)”
In September 2024 Manning Publications published his Build a Large Language Model (From Scratch), a 368-page book.[11]
The publisher’s author bio described him as a staff research engineer at Lightning AI building and training large language models, previously an assistant professor of statistics at the University of Wisconsin–Madison.[12]
c. 2025: Leaves Lightning AI to Work Independently
He has said that after about three years at Lightning AI he wanted to try something new and started his own small company, doing collaborative implementation work, educational videos and writing, though he does not consider himself a full-time author.[10]
January 31, 2026Appears on the Lex Fridman Podcast
He appeared with Nathan LambertNathan LambertNathan Lambert is a machine learning researcher focused on large language model post-training and reinforcement learning from human feedback (RLHF), who worked on open models such as Zephyr, OLMo and Tülu at Hugging Face and Ai2, writes the Interconnects newsletter and an RLHF textbook, and co-founded the nonprofit Trillium Labs in 2026.Open the full entry in episode 490 of the Lex FridmanLex FridmanLex Fridman is a Soviet-born, US-raised computer scientist and podcast host who works as an MIT research scientist on human-AI interaction and autonomous driving. His Lex Fridman Podcast is known for hours-long conversations with guests including heads of state and technology leaders.Open the full entry Podcast, whose page names him as author of two “From Scratch” books; topics included AI for coding, scaling laws and advice for getting into AI.[13]
2026Co-Authors the MiCA Paper with Sten Rüdiger
In 2026 he and Sten Rüdiger posted the paper “MiCA Learns More Knowledge Than LoRA and Full Fine-Tuning” on arXiv.[14]
June 2026Publishes “Build a Reasoning Model (From Scratch)”
In June 2026 Manning published his Build a Reasoning Model (From Scratch), a 440-page book available in translations including Simplified Chinese, Complex Chinese, German, Japanese and Korean.[15]
September–October 2026: Launches Reasoning-Model Courses
In September 2026 he released a roughly 90-minute course on reasoning models on LinkedInLinkedInLinkedIn is a social networking platform for professionals. It was founded in 2002 by Reid Hoffman and others, launched in 2003, and listed on the New York Stock Exchange in 2011; after Microsoft acquired it for approximately $26.2 billion in 2016, it became a wholly owned Microsoft subsidiary. Its revenue comes from membership subscriptions, advertising, and recruitment solutions.Open the full entry Learning, and on October 24 he published more than 11 hours of coding videos on building reasoning models, covering evaluation, inference-time scaling, reinforcement learning and distillation.[16]
As of October 2026: LLM Research Engineer and Educator
As of October 2026 he describes himself as an LLM research engineer who reads papers and reference implementations and then builds smaller versions in PyTorch to understand models.[17]
His newsletter Ahead of AI says it is read by more than 200,000 researchers and practitioners.[18]
The companion repository rasbt/LLMs-from-scratch has about 107,000 stars on GitHub.[19]
Related Organizations, Websites, and Public Accounts
Personal website: Public link: https://sebastianraschka.com/ (opens in a new window)[16]
X: Public account: https://x.com/rasbt (opens in a new window)[16]
LinkedIn: Public profile: https://www.linkedin.com/in/sebastianraschka/ (opens in a new window)[16]
YouTubeYouTubeYouTube is Google’s video-sharing and creator platform, founded in 2005 by Steve Chen, Chad Hurley, and Jawed Karim and acquired by Google in 2006. Built around video uploading, viewing, and creator earnings, the platform has developed Shorts, YouTube Music, Premium, YouTube TV, and products for children, and is headquartered in San Bruno, California, United States.Open the full entry: Public channel: https://www.youtube.com/c/SebastianRaschka (opens in a new window)[17]
Lightning AI: Official website: https://lightning.ai/ (opens in a new window)[7]
University of Wisconsin-Madison: Official website: https://www.wisc.edu/ (opens in a new window)[7]
Sources
- New Faculty Focus: Sebastian Raschka (opens in a new window)
- Chapter 12. Sebastian Raschka (opens in a new window)
- About the Author - Python Machine Learning [Book] (opens in a new window)
- PyData Chicago 2016 | Sebastian Raschka (opens in a new window)
- MLxtend: Providing machine learning and data science utilities and extensions to Python's scientific computing stack (opens in a new window)
- Biology and Deep Learning (opens in a new window)
- Courses | Sebastian Raschka, PhD (opens in a new window)
- Books | Sebastian Raschka, PhD (opens in a new window)
- Hands-On Machine Learning Education with Sebastian Raschka (opens in a new window)
- Do engineers still need to understand how LLMs work? (opens in a new window)
- Build a Large Language Model (From Scratch) (opens in a new window)
- about the author · Build a Large Language Model (From Scratch) (opens in a new window)
- #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI | Lex Fridman Podcast (opens in a new window)
- Publications & Research | Sebastian Raschka, PhD (opens in a new window)
- Build a Reasoning Model (From Scratch) - Sebastian Raschka (opens in a new window)
- Sebastian Raschka, LLM Research Engineer | Sebastian Raschka, PhD (opens in a new window)
- About Sebastian Raschka | Sebastian Raschka, PhD (opens in a new window)
- About - Ahead of AI (opens in a new window)
- GitHub - rasbt/LLMs-from-scratch: Implement a ChatGPT-like LLM in PyTorch from scratch, step by step · GitHub (opens in a new window)