| Python Machine Learning, 3rd Edition S Raschka, V Mirjalili Packt Publishing Ltd., 2019 | 3358* | 2019 |
| Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning S Raschka arXiv preprint arXiv:1811.12808, 2018 | 1200 | 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 | 665 | 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 | 586 | 2020 |
| Naive Bayes and Text Classification I - Introduction and Theory S Raschka arXiv preprint arXiv:1410.5329, 2014 | 269 | 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 | 260 | 2020 |
| Python Machine Learning S Raschka Packt Publishing, 2015 | 207* | 2015 |
| Model evaluation, model selection, and algorithm selection in machine learning. arXiv 2018 S Raschka arXiv preprint arXiv:1811.12808, 1811 | 176 | 1811 |
| Machine Learning with PyTorch and Scikit-Learn S Raschka, YH Liu, V Mirjalili Packt Publishing Ltd., 2022 | 143 | 2022 |
| 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 | 125 | 2018 |
| An Overview of General Performance Metrics of Binary Classifier Systems S Raschka arXiv preprint arXiv:1410.5330, 2014 | 112 | 2014 |
| About feature scaling and normalization S Raschka Sebastian Raschka. Disques, nd Web. Dec, 2014 | 103* | 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 | 98 | 2020 |
| Linear Discriminant Analysis bit by bit S Raschka Blog, August, 2014 | 89* | 2014 |
| Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition S Raschka, B Kaufman Methods 180, 89-110, 2020 | 71 | 2020 |
| 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 | 68* | 2018 |
| Pdf Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, by S Raschka | 68 | 2017 |
| BioPandas: Working with molecular structures in pandas DataFrames S Raschka The Journal of Open Source Software 2 (14), 2017 | 58 | 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 | 54 | 2018 |
| FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers V Mirjalili, S Raschka, A Ross IEEE Access, 2019 | 51 | 2019 |
Dr. Vahid MirjaliliResearch ScientistVerified email at mmm.com
