Discover @rasbt Open Source projects

Sebastian Raschka (@rasbt)

rasbt

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deeplearning-models

A collection of various deep learning architectures, models, and tips

Jupyter Notebook

python-machine-learning-book

The "Python Machine Learning (1st edition)" book code repository and info resource

Jupyter Notebook

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

Jupyter Notebook

mlxtend

A library of extension and helper modules for Python's data analysis and machine learning libraries.

python-machine-learning-book-3rd-edition

The "Python Machine Learning (3rd edition)" book code repository

Jupyter Notebook

pattern_classification

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

Jupyter Notebook

python_reference

Useful functions, tutorials, and other Python-related things

Jupyter Notebook

deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

Jupyter Notebook

machine-learning-book

Code Repository for Machine Learning with PyTorch and Scikit-Learn

Jupyter Notebook

matplotlib-gallery

Examples of matplotlib codes and plots

Jupyter Notebook

watermark

An IPython magic extension for printing date and time stamps, version numbers, and hardware information

machine-learning-notes

Collection of useful machine learning codes and snippets (originally intended for my personal use)

Jupyter Notebook

stat479-machine-learning-fs19

Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison

Jupyter Notebook

scipy2023-deeplearning

Jupyter Notebook

pyprind

PyPrind - Python Progress Indicator Utility

stat453-deep-learning-ss20

STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2020)

Jupyter Notebook

stat479-deep-learning-ss19

Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison

Jupyter Notebook

algorithms_in_ipython_notebooks

A repository with IPython notebooks of algorithms implemented in Python.

Jupyter Notebook

stat479-machine-learning-fs18

Course material for STAT 479: Machine Learning (FS 2018) at University Wisconsin-Madison

Jupyter Notebook

musicmood

A machine learning approach to classify songs by mood.

stat453-deep-learning-ss21

STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2021)

Jupyter Notebook

stat451-machine-learning-fs20

STAT 451: Intro to Machine Learning @ UW-Madison (Fall 2020)

Jupyter Notebook

datacollect

A collection of tools to collect and download various data.

Jupyter Notebook

data-science-tutorial

Code material for a data science tutorial

Jupyter Notebook

LLM-finetuning-scripts

Jupyter Notebook

One-Python-benchmark-per-day

An ongoing fun challenge where I'll try to post one Python benchmark per day.

pydata-chicago2016-ml-tutorial

Machine learning with scikit-learn tutorial at PyData Chicago 2016

Jupyter Notebook

stat451-machine-learning-fs21

Jupyter Notebook

cvpr2023

faster-pytorch-blog

Outlining techniques for improving the training performance of your PyTorch model without compromising its accuracy

msu-datascience-ml-tutorial-2018

Machine learning with Python tutorial at MSU Data Science 2018

Jupyter Notebook

protein-science

A collection of useful tutorials for Protein Science

markdown-toclify

A Python command line tool that creates a Table of Contents for Markdown documents

cyclemoid-pytorch

Cyclemoid implementation for PyTorch

MachineLearning-QandAI-book

Machine Learning Q and AI book

Jupyter Notebook

pydata-annarbor2017-dl-tutorial

Code snippets for "Introduction to Deep Learning with TensorFlow" at PyData Ann Arbor Aug 2017

Jupyter Notebook

smilite

A Python module to retrieve and compare SMILE strings of chemical compounds from the free ZINC online database

pytorch-memory-optim

This code repository contains the code used for my "Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorch" blog post.

DeepLearning-Gdansk2019-tutorial

Ordinal Regression tutorial for the International Summer School on Deep Learning 2019

Jupyter Notebook

model-eval-article-supplementary

Supplementary material for the article "Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning"

Jupyter Notebook

nn_plus_gzip

Gzip and nearest neighbors for text classification

Jupyter Notebook

LLMs-from-scratch

Implementing ChatGPT-like LLMs from scratch, step by step

Jupyter Notebook

interpretable-ml-article

Code examples for my Interpretable Machine Learning Blog Series

Jupyter Notebook

R_snippets

R Scripts for general data analysis and plotting

numpy-intro-blogarticle-2020

Jupyter Notebook for the "Scientific Computing in Python: Introduction to NumPy and Matplotlib" blog article

Jupyter Notebook

blog-finetuning-llama-adapters

Supplementary material for "Understanding Parameter-Efficient Finetuning of Large Language Models: From Prefix Tuning to Adapters"

Jupyter Notebook

mputil

Utility functions for Python's multiprocessing standard library module

pybibtex

Utility functions for parsing BibTeX files and creating citation reference lists.

mytorch

Collection of PyTorch-related utility functions

posit2023-python-ml

Workshop materials for posit::conf(2023)

Jupyter Notebook

comparing-automatic-augmentation-blog

Comparing four automatic image augmentation techniques in PyTorch: AutoAugment, RandAugment, AugMix, and TrivialAugment

Jupyter Notebook

pytorch-fabric-demo

Hbind

Calculates hydrogen-bond interaction tables for protein-small molecule complexes, based on protein PDB and protonated ligand MOL2 structure input. Raschka et al. (2018) J. Computer-Aided Molec. Design

scipy2022-talk

screenlamp

screenlamp is a Python toolkit for hypothesis-driven virtual screening

gradient-accumulation-blog

Finetuning BLOOM on a single GPU using gradient-accumulation

2021-issdl-gdansk

Intro to GAN Tutorial for the International Summer School of Deep Learning 2021 in Gdansk

Jupyter Notebook

uw-madison-datacience-club-talk-oct2019

Slides and code for the talk at UW-Madison's Data Science Club, 10 Oct 2019

Jupyter Notebook

predicting-activity-by-machine-learning

Activity From Virtual Screening Code Repository

Jupyter Notebook

BondPack

A collection of PyMOL plugins to visualize atomic bonds.

siteinterlock

A novel approach to pose selection in protein-ligand docking based on graph theory.

low-rank-adaptation-blog

R-notes

Various R lang related material for teaching.

2021-pydata-jeddah

Materials for "Transformers from the Ground Up" at PyData Jeddah on August 5, 2021

Jupyter Notebook

b3-basic-batchsize-benchmark

Experiments for the blog post "No, We Don't Have to Choose Batch Sizes As Powers Of 2"

ViT-finetuning-scripts

Vision transformer finetuning scripts

datapipes-blog

Code for the DataPipes article

Jupyter Notebook

srgan-lightning-blog

Sharing Deep Learning Research Models with Lightning Part 1: Building A Super Resolution App

try-lion-optimizer

Jupyter Notebook

mnist-pngs

MNIST files in PNG format

py-args

Python command line tools as productivity supplements for Posix systems

ecml-teaching-ml-2021

Jupyter Notebook

HbindViz

Tools for generating hydrogen-bond interaction visualizations from Hbind

protein-recognition-index

Protein Recognition Index (PRI), measuring the similarity between H-bonding features in a given complex (predicted or designed) and the characteristic H-bond trends from crystallographic complexes

ord-torchhub

Ordinal Regression PyTorch Hub

compair

Model evaluation utilities

torchmetrics-blog

Code for "TorchMetrics -- How do we use it, and what's the difference between .update() and .forward()"

Jupyter Notebook

rasbt

advent-of-code-2016

My Solutions for the Advent of Code 2016

bugreport

A repository to store code examples to reproduce issues for bug reports.

Jupyter Notebook

bookgiveaway-2022-wordcloud

Word cloud from the results of the book-giveaway

Jupyter Notebook

pycon2024

Tutorial Materials for "The Fundamentals of Modern Deep Learning with PyTorch"