ProceedingsSciPy ProceedingsContent License: Creative Commons Attribution 3.0 Unported (CC-BY-3.0)Credit must be given to the creatorProceedings of the 18th Python in Science ConferenceSciPy 2019, Austin, Texas July 8 - July 14July 8, 2019https://doi.org/10.25080/Majora-7ddc1dd1-026Download PDFDownload BibtexSupporting DocumentsOrganizationPosters and SlidesSponsored StudentsAccepted Papers¶Accelerating the Advancement of Data Science EducationAccelerating the Advancement of Data Science EducationEric Van Dusen, Anthony Suen, Alan Liang, +1https://doi.org/10.25080/Majora-7ddc1dd1-000Case study: Real-world machine learning application for hardware failure detectionCase study: Real-world machine learning application for hardware failure detectionHongsup Shinhttps://doi.org/10.25080/Majora-7ddc1dd1-001Expert RF Feature Extraction to Win the Army RCO AI Signal Classification ChallengeExpert RF Feature Extraction to Win the Army RCO AI Signal Classification ChallengeKyle Logue, Esteban Valles, Andres Vila, +5https://doi.org/10.25080/Majora-7ddc1dd1-002Deep and Ensemble Learning to Win the Army RCO AI Signal Classification ChallengeDeep and Ensemble Learning to Win the Army RCO AI Signal Classification ChallengeAndres Vila, Donna Branchevsky, Kyle Logue, +5https://doi.org/10.25080/Majora-7ddc1dd1-003Analyzing Particle Systems for Machine Learning and Data Visualization with freudAnalyzing Particle Systems for Machine Learning and Data Visualization with freudBradley Dice, Vyas Ramasubramani, Eric Harper, +3https://doi.org/10.25080/Majora-7ddc1dd1-004CAF Implementation on FPGA Using Python ToolsCAF Implementation on FPGA Using Python ToolsChiranth Siddappa, Mark Wickerthttps://doi.org/10.25080/Majora-7ddc1dd1-005Developing a Graph Convolution-Based Analysis Pipeline for Multi-Modal Neuroimage Data: An Application to Parkinson’s DiseaseDeveloping a Graph Convolution-Based Analysis Pipeline for Multi-Modal Neuroimage Data: An Application to Parkinson’s DiseaseChristian McDaniel, Shannon Quinnhttps://doi.org/10.25080/Majora-7ddc1dd1-006pyjanitor: A Cleaner API for Cleaning Datapyjanitor: A Cleaner API for Cleaning DataEric J., Zachary Barry, Sam Zuckerman, +1https://doi.org/10.25080/Majora-7ddc1dd1-007Codebraid: Live Code in Pandoc MarkdownCodebraid: Live Code in Pandoc MarkdownGeoffrey Poorehttps://doi.org/10.25080/Majora-7ddc1dd1-008Solving Polynomial Systems with phcpySolving Polynomial Systems with phcpyJasmine Otto, Angus Forbes, Jan Verscheldehttps://doi.org/10.25080/Majora-7ddc1dd1-009Optimizing Python-Based Spectroscopic Data Processing on NERSC SupercomputersOptimizing Python-Based Spectroscopic Data Processing on NERSC SupercomputersLaurie Stephey, Rollin Thomas, Stephen Baileyhttps://doi.org/10.25080/Majora-7ddc1dd1-00aA Real-Time 3D Audio Simulator for Cognitive Hearing ScienceA Real-Time 3D Audio Simulator for Cognitive Hearing ScienceMark Wickerthttps://doi.org/10.25080/Majora-7ddc1dd1-00bAn intelligent shopping list based on the application of partitioning and machine learning algorithmsAn intelligent shopping list based on the application of partitioning and machine learning algorithmsNadia Tahiri, Bogdan Mazoure, Vladimir Makarenkovhttps://doi.org/10.25080/Majora-7ddc1dd1-00cParameter Estimation Using the Python Package pymcmcstatParameter Estimation Using the Python Package pymcmcstatPaul Miles, Ralph Smithhttps://doi.org/10.25080/Majora-7ddc1dd1-00dPyLZJD: An Easy to Use Tool for Machine LearningPyLZJD: An Easy to Use Tool for Machine LearningEdward Raff, Joe Aurelio, Charles Nicholashttps://doi.org/10.25080/Majora-7ddc1dd1-00eParkinson’s Classification and Feature Extraction from Diffusion Tensor ImagesParkinson’s Classification and Feature Extraction from Diffusion Tensor ImagesRajeswari Sivakumar, Shannon Quinnhttps://doi.org/10.25080/Majora-7ddc1dd1-00fPyDDA: A new Pythonic Wind Retrieval PackagePyDDA: A new Pythonic Wind Retrieval PackageRobert Jackson, Scott Collis, Timothy Lang, +2https://doi.org/10.25080/Majora-7ddc1dd1-010Better and faster hyperparameter optimization with DaskBetter and faster hyperparameter optimization with DaskScott Sievert, Tom Augspurger, Matthew Rocklinhttps://doi.org/10.25080/Majora-7ddc1dd1-011Visualization of Bioinformatics Data with Dash BioVisualization of Bioinformatics Data with Dash BioShammamah Hossainhttps://doi.org/10.25080/Majora-7ddc1dd1-012PMDA - Parallel Molecular Dynamics AnalysisPMDA - Parallel Molecular Dynamics AnalysisShujie Fan, Max Linke, Ioannis Paraskevakos, +3https://doi.org/10.25080/Majora-7ddc1dd1-013Proceedings of the 18th Python in Science ConferenceOrganization
