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Sebastian Raschka

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Sebastian Raschka


Born
in Herne, Germany
April 07, 1988

Website

Twitter

Genre


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

Recommendations for Getting the Most Out of a Technical Book

This short article compiles a few notes I previously shared when readers ask how to get the most out of my building large language model from scratch books. I follow a similar approach when I read technical books myself. It is not meant as a universal recipe, but it may be a helpful starting point. For this particular book, I strongly suggest reading it in order since each chapter depends on the p Read more of this blog post »
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Published on November 11, 2025 16:08
Average rating: 4.33 · 1,182 ratings · 94 reviews · 31 distinct worksSimilar authors
Python Machine Learning

4.25 avg rating — 755 ratings — published 2015 — 22 editions
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Build a Large Language Model

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Machine Learning Q and AI: ...

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Python: Deeper Insights int...

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Instant Heat Maps in R How-to

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Python機器學習

really liked it 4.00 avg rating — 2 ratings
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Machine Learning con PyTorc...

it was amazing 5.00 avg rating — 1 rating2 editions
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Python. Machine learning i ...

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Python機械学習プログラミング 達人データサイエン...

liked it 3.00 avg rating — 1 rating2 editions
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Quotes by Sebastian Raschka  (?)
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“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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