Search Results - "supervised"

Pharmacovigilance Volume 2

Subjects: “…supervised learning…”
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Geschlecht und Geschlechtergerechtigkeit in der Supervision Eine Diskursanalyse by Bredemann, Miriam

Subjects: “…Studien zu Supervision…”
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Geschlecht und Geschlechtergerechtigkeit in der Supervision Eine Diskursanalyse by Bredemann, Miriam

Subjects: “…Studien zu Supervision…”
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Statistical Analysis of Networks by Avrachenkov, Konstantin

Subjects: “…Network analysis, statistical analysis, network modeling, community detection, graph-based semi-supervised learning, sampling in networks…”
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Addiction, Modernity, and the City A Users' Guide to Urban Space by Smith, Christopher B.R

Subjects: “…abject;body;capitalist;cityscape;consumption;narcotic;paradigm;pathology;supervised;urban…”
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Statistical Analysis of Networks by Avrachenkov, Konstantin

Subjects: “…Network analysis, statistical analysis, network modeling, community detection, graph-based semi-supervised learning, sampling in networks…”
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Addiction, Modernity, and the City A Users' Guide to Urban Space by Smith, Christopher B.R

Subjects: “…abject;body;capitalist;cityscape;consumption;narcotic;paradigm;pathology;supervised;urban…”
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Überwachte Methoden für die spektrale Entmischung mit künstlichen neuronalen Netzen by Anastasiadis, Johannes

Subjects: “…data generation; data augmentation; supervised training; artificial neural network; hyperspectral image; Datenerzeugung; Datenaugmentierung; überwachtes Training; Hyperspektralbild; künstliche neuronale Netze…”
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Self-Supervised Learning for Visual Obstacle Avoidance Technical report by van Dijk, Tom

Subjects: “…self-supervised learning…”
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Convex Optimization for Machine Learning by Suh, Changho

Subjects: “…Convex Optimization, Deep Learning, Generative Adversarial Networks (GANs), TensorFlow, Supervised Learning, Wasserstein GAN, Strong Duality, Weak Duality, Computed Tomography…”
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Convex Optimization for Machine Learning by Suh, Changho

Subjects: “…Convex Optimization, Deep Learning, Generative Adversarial Networks (GANs), TensorFlow, Supervised Learning, Wasserstein GAN, Strong Duality, Weak Duality, Computed Tomography…”
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Überwachte Methoden für die spektrale Entmischung mit künstlichen neuronalen Netzen by Anastasiadis, Johannes

Subjects: “…data generation; data augmentation; supervised training; artificial neural network; hyperspectral image; Datenerzeugung; Datenaugmentierung; überwachtes Training; Hyperspektralbild; künstliche neuronale Netze…”
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Internet basierte Ausbildungssupervision by Ziemons, Michael

Subjects: “…Supervision;Internet;Hochschuldiddaktik…”
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Internet basierte Ausbildungssupervision by Ziemons, Michael

Subjects: “…Supervision;Internet;Hochschuldiddaktik…”
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Learning to Quantify by Esuli, Andrea

Subjects: “…Supervised Learning…”
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Learning to Quantify by Esuli, Andrea

Subjects: “…Supervised Learning…”
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Chapter AI for Improving the Overall Equipment Efficiency in Manufacturing Industry by Echeverria, Lluis

Subjects: “…machine learning, supervised learning, unsupervised learning, classification, regression, ensembles, artificial intelligence, data mining, data-driven, industry 4.0, smart manufacturing, cyber-physical systems, predictive analytics…”
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Chapter AI for Improving the Overall Equipment Efficiency in Manufacturing Industry by Echeverria, Lluis

Subjects: “…machine learning, supervised learning, unsupervised learning, classification, regression, ensembles, artificial intelligence, data mining, data-driven, industry 4.0, smart manufacturing, cyber-physical systems, predictive analytics…”
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Information Theory for Data Science by Suh, Changho

Subjects: “…Information Theory, Data Science, Source Coding, Channel Coding, DNA sequencing, DNA sequencing, Top-K ranking, Supervised learning, Unsupervised Learning, Generative Adversarial Networks (GANs), TensorFlow…”
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Information Theory for Data Science by Suh, Changho

Subjects: “…Information Theory, Data Science, Source Coding, Channel Coding, DNA sequencing, DNA sequencing, Top-K ranking, Supervised learning, Unsupervised Learning, Generative Adversarial Networks (GANs), TensorFlow…”
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