Sebastian Raschka
Sebastian Raschka
Lead AI Educator at Lightning AI, Asst. Professor of Statistics, University of Wisconsin-Madison
Verified email at - Homepage
Cited by
Cited by
Python Machine Learning, 3rd Edition
S Raschka, V Mirjalili
Packt Publishing Ltd., 2019
Python Machine Learning
S Raschka
Packt Publishing, 2015
Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
S Raschka
arXiv preprint arXiv:1811.12808, 2018
MLxtend: Providing machine learning and data science utilities and extensions to Python’s scientific computing stack
S Raschka
Journal of open source software 3 (24), 638, 2018
Machine learning in python: Main developments and technology trends in data science, machine learning, and artificial intelligence
S Raschka, J Patterson, C Nolet
Information 11 (4), 193, 2020
Naive Bayes and Text Classification I - Introduction and Theory
S Raschka
arXiv preprint arXiv:1410.5329, 2014
Rank consistent ordinal regression for neural networks with application to age estimation
W Cao, V Mirjalili, S Raschka
Pattern Recognition Letters 140, 325-331, 2020
Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images
V Mirjalili, S Raschka, A Namboodiri, AR Ross
11th IAPR International Conference on Biometrics (ICB 2018), 2018
Machine Learning with PyTorch and Scikit-Learn
S Raschka, YH Liu, V Mirjalili
Packt Publishing Ltd., 2022
An Overview of General Performance Metrics of Binary Classifier Systems
S Raschka
arXiv preprint arXiv:1410.5330, 2014
About feature scaling and normalization
S Raschka
Sebastian Raschka. Disques, nd Web. Dec, 2014
Linear Discriminant Analysis bit by bit
S Raschka
Blog, August, 2014
PrivacyNet: Semi-adversarial networks for multi-attribute face privacy
V Mirjalili, S Raschka, A Ross
IEEE Transactions on Image Processing 29, 9400-9412, 2020
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition
S Raschka, B Kaufman
Methods 180, 89-110, 2020
Pdf Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, by
S Raschka
Machine Learning mit Python und Scikit-learn und TensorFlow: das umfassende Praxis-Handbuch für Data Science, Deep Learning und Predictive Analytics
S Raschka, V Mirjalili, K Lorenzen
mitp, 2018
BioPandas: Working with molecular structures in pandas DataFrames
S Raschka
The Journal of Open Source Software 2 (14), 2017
Protein–ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and …
S Raschka, AJ Wolf, J Bemister-Buffington, LA Kuhn
Journal of computer-aided molecular design 32, 511-528, 2018
Gender privacy: An ensemble of semi adversarial networks for confounding arbitrary gender classifiers
V Mirjalili, S Raschka, A Ross
2018 IEEE 9th International Conference on Biometrics Theory, Applications …, 2018
FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers
V Mirjalili, S Raschka, A Ross
IEEE Access, 2019
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