Ohcanbohtosat - "Machine learning"

Machine Learning Advanced Techniques and Emerging Applications

Fáttát: “…Machine learning bicssc…”
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Machine Learning Algorithms, Models and Applications

Fáttát: “…Machine learning bicssc…”
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Machine Learning

Fáttát: “…Machine learning…”
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Machine Learning

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Automated Machine Learning Methods, Systems, Challenges /

“…The Springer Series on Challenges in Machine Learning,…”
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Applied Machine Learning

Fáttát: “…machine learning…”
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Machine Learning and Biometrics

Fáttát: “…Machine learning bicssc…”
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Automated Machine Learning Methods, Systems, Challenges

“…The Springer Series on Challenges in Machine Learning…”
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Application of Machine Learning

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Machine Learning in Insurance

Fáttát: “…machine learning…”
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Machine Learning in Tribology

Fáttát: “…machine learning…”
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Automated Machine Learning Methods, Systems, Challenges

“…The Springer Series on Challenges in Machine Learning…”
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Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study Dahkki Visweswaran, Shyam, Colditz, Jason B, O'Halloran, Patrick, Han, Na-Rae, Taneja, Sanya B, Welling, Joel, Chu, Kar-Hai, Sidani, Jaime E, Primack, Brian A

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Machine Learning for Brain Disorders

Sisdoallologahallan: “…A Non-Technical Introduction to Machine Learning -- Classic Machine Learning Methods -- Deep Learning: Basics and Convolutional Neural Networks (CNN) -- Recurrent Neural Networks (RNN) - Architectures, Training Tricks, and Introduction to Influential Research -- Generative Adversarial Networks and Other Generative Models -- Transformers and Visual Transformers -- Clinical Assessment of Brain Disorders -- Neuroimaging in Machine Learning for Brain Disorders -- Electroencephalography and Magnetoencephalography -- Working with Omics Data, An Interdisciplinary Challenge at the Crossroads of Biology and Computer Science -- Electronic Health Records as Source of Research Data -- Mobile Devices, Connected Objects, and Sensors -- Medical Image Segmentation using Deep Learning -- Image Registration: Fundamentals and Recent Advances Based on Deep Learning -- Computer-Aided Diagnosis and Prediction in Brain Disorders -- Subtyping Brain Diseases from Imaging Data -- Data-Driven Disease Progression Modelling -- Computational Pathology for Brain Disorders -- Integration of Multimodal Data -- Evaluating Machine Learning Models and their Diagnostic Value -- Reproducibility in Machine Learning for Medical Imaging -- Interpretability of Machine Learning Methods Applied to Neuroimaging -- A Regulatory Science Perspective on Performance Assessment of Machine Learning Algorithms in Imaging -- Main Existing Datasets for Open Brain Research on Humans -- Machine Learning for Alzheimer's Disease and Related Dementias -- Machine Learning for Parkinson's Disease and Related Disorders -- Machine Learning in Neuroimaging of Epilepsy -- Machine Learning in Multiple Sclerosis -- Machine Learning for Cerebrovascular Disorders -- The Role of Artificial Intelligence in Neuro-Oncology Imaging -- Machine Learning for Neurodevelopmental Disorders -- Machine Learning and BrainImaging for Psychiatric Disorders: New Perspectives.…”
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Machine Learning for Brain Disorders

Fáttát: “…machine learning…”
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27: Machine learning and law Dahkki Porębski, Andrzej

Fáttát: “…Machine learning; Predictive justice; XAI; COMPAS system; IT in the legal domain; Artificial intelligence…”
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New Advances in Machine Learning

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Social Media and Machine Learning

Fáttát: “…Machine learning…”
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Machine Learning for Energy Systems

Fáttát: “…machine learning…”
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Machine Learning in Biomolecular Simulations

Fáttát: “…machine learning…”
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