Sebastian Raschka

LLMs From Scratch. I built a step-by-step guide to creating your own ChatGPT-like AI model.

Python Machine Learning. I wrote a machine learning book with 400 pages of code you can actually use.

Reasoning from Scratch. I built a step-by-step guide to creating an AI model that reasons through problems.

Machine Learning with PyTorch and Scikit-Learn. I wrote code notebooks teaching machine learning with two popular tools.

Mlxtend. I made a toolbox that handles the repetitive parts of data science work.

LLM Architecture Gallery. I made a visual gallery of how AI models are structured.

Machine Learning Q and AI. I wrote a book answering thirty essential questions about AI and machine learning.

BioPandas. I made a tool that loads protein structures into spreadsheets.

Mini Coding Agent. I built a minimal coding agent that explains how AI assistants write code.

Deep Learning Models. I collected working AI models with step-by-step explanations you can run.

Watermark. I made a tool that stamps your Jupyter notebooks with dates and system information.

LLM Workshop 2024. I made a workshop teaching how AI language models work from the ground up.

Coral. I made AI tools that understand ordered predictions like age ranges.

Stat 451. I made a complete machine learning course with runnable code notebooks.

Pattern Classification. I wrote tutorials that teach machine learning through working examples.

RAGs. I made working examples of AI systems that search and answer from documents.

PyTorch Deep Learning Workshop. I created tutorial materials teaching deep learning to Python programmers.

Local Coding Agent Evals. I made tests to compare AI coding assistants running on your own machine.

Math Dataset. I made a math problem dataset with the test set removed.

Gemma Walkthrough. I built a hands-on guide to understanding how AI models work inside.

Model Tuner. I made notebooks that teach AI models to learn from your own data.

Sebastian Raschka. I write about AI research and share practical open-source tools.

SciPy 2023 Deep Learning Workshop. I made a workshop teaching deep learning with PyTorch for non-specialists.

Dora From Scratch. I wrote step-by-step code showing how to customize AI models efficiently.

Python Machine Learning. I wrote code examples for a machine learning textbook.

ML Notes. I collected machine learning code snippets I use all the time.

Python Reference. I collected Python tips, tutorials, and useful code snippets.

CVPR 2023 Training Guide. I wrote a tutorial for speeding up AI model training with minimal code changes.

Bugreport. I made a repository for storing code examples that reproduce bugs.

PDF Splitter. I built a native Mac app that splits PDFs into individual pages and images.

PyTorch Memory Optimizer. I wrote code showing how to train large AI models without maxing out your memory.

Python ML Workshop. I created workshop materials teaching machine learning with Python.

Classifier. I built text classification that needs no model training.

ViT Finetuning. I wrote scripts that teach image models to recognize your own pictures.

Deep Learning Course. I compiled a university course teaching deep learning to non-specialists.

Faster PyTorch. I wrote techniques for training AI models faster without sacrificing accuracy.

Py-Args. I built a tool that renames and finds-replaces a huge pile of files at once.

Adapter Guide. I wrote a guide explaining how to customize AI models efficiently.

test-github-image-rendering. Debug GitHub rendering issues

Machine Learning Course. I made a complete machine learning course with working examples.

Low-Rank Adaptation. I wrote a guide explaining how to adapt AI models efficiently.

Gradient Accumulation. I showed how to train a huge AI model on one regular computer.

Machine Learning Course. I organized a complete machine learning course with lectures and exercises.

Batch Size Benchmark. I tested whether AI models need powers-of-2 batch sizes.

Python Machine Learning. I wrote a complete guide to machine learning with working code examples.

Mputil. I made utility functions for Python that process data faster by running tasks in parallel.

TorchMetrics Guide. I wrote a guide explaining how to measure AI model performance correctly.

Compair. I made tools to measure and compare how well AI models perform.

DataPipes. I wrote working examples for loading data into machine learning projects.

PyData Chicago 2016 ML Tutorial. I created a machine learning tutorial with code examples and slides.