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Sebastian Raschka

Born

in Herne, Germany

April 07, 1988

Website

http://sebastianraschka.com

Twitter

rasbt

Genre

Science, Nonfiction, Ebooks

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Some of my greatest passions are "Data Science" and machine learning. I enjoy everything that involves working with data: The discovery of interesting patterns and coming up with insightful conclusions using techniques from the fields of data mining and machine learning for predictive modeling.

I am a big advocate of working in teams and the concept of "open source." In my opinion, it is a positive feedback loop: Sharing ideas and tools that are useful to others and getting constructive feedback that helps us learn!

A little bit more about myself: Currently, I am sharpening my analytical skills as a PhD candidate at Michigan State University where I am currently working on a highly efficient virtual screening software for computer-aided drug- ...more

148 posts
Sebastian Raschka's Blog

Sebastian Raschka isn't a Goodreads Author (yet), but they do have a blog, so here are some recent posts imported from their feed.

Language Models for Text Classification: From Bag-of-Words to Jev

A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency

View more on Sebastian Raschka's website »

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Published on September 29, 2026 03:50

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Sebastian Raschka’s books

Average rating: 4.35 · 1,401 ratings · 128 reviews · 34 distinct works • Similar authors

	Python Machine Learning 4.24 avg rating — 761 ratings — published 2015 — 22 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Build a Large Language Model 4.57 avg rating — 399 ratings — 4 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python by Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili 4.40 avg rating — 122 ratings — 3 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI 4.27 avg rating — 55 ratings — 4 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Build a Reasoning Model 4.56 avg rating — 32 ratings — 3 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python by Sebastian Raschka, David Julian, John Hearty 3.69 avg rating — 16 ratings — 3 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Instant Heat Maps in R How-to 4.63 avg rating — 8 ratings — published 2013 — 4 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Python機器學習 really liked it 4.00 avg rating — 2 ratings	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Machine Learning con PyTorch y Scikit-Learn it was amazing 5.00 avg rating — 1 rating — 2 editions	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
	Build a Reasoning Model it was amazing 5.00 avg rating — 1 rating	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars

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Quotes by Sebastian Raschka (?)

“Eventually, the performance of a classifier, computational power as well as predictive power, depends heavily on the underlying data that are available for learning. The five main steps that are involved in training a machine learning algorithm can be summarized as follows: Selection of features. Choosing a performance metric. Choosing a classifier and optimization algorithm. Evaluating the performance of the model. Tuning the algorithm.”
― Sebastian Raschka, Python Machine Learning: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics

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“example,”
― Sebastian Raschka, Python Machine Learning: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics

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“computationally”
― Sebastian Raschka, Python Machine Learning: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics

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