6 citations · 9 across the 3 of their papers we have counts for
10 papers
Deeper Learning By Doing: Integrating Hands-On Research Projects Into a Machine Learning Course
Sebastian Raschka
Machine learning has seen a vast increase of interest in recent years, along with an abundance of learning resources. While conventional lectures provide students with important in…
Looking back to lower-level information in few-shot learning
Zhongjie Yu, Sebastian Raschka
Humans are capable of learning new concepts from small numbers of examples. In contrast, supervised deep learning models usually lack the ability to extract reliable predictive rul…
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence
Sebastian Raschka, Joshua Patterson, Corey Nolet
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the to…
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition
Sebastian Raschka, Benjamin Kaufman
In the last decade, machine learning and artificial intelligence applications have received a significant boost in performance and attention in both academic research and industry.…
PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy
Vahid Mirjalili, Sebastian Raschka, Arun Ross
Recent research has established the possibility of deducing soft-biometric attributes such as age, gender and race from an individual's face image with high accuracy. However, this…
FlowSAN: Privacy-enhancing Semi-Adversarial Networks to Confound Arbitrary Face-based Gender Classifiers
Vahid Mirjalili, Sebastian Raschka, Arun Ross
Privacy concerns in the modern digital age have prompted researchers to develop techniques that allow users to selectively suppress certain information in collected data while allo…