Search Results - (((((((want OR wantsa) OR ken) OR mantis) OR cantor) OR anne) OR carter) OR wanting) algorithms.

  1. 61

    Advanced Analytics with R and Tableau. by Stirrup, Jen

    Published 2016
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  2. 62

    Focus on artificial neural networks

    Published 2011
    Table of Contents: “…ARTIFICIAL NEURAL NETWORKS (ANNS) -- 3. MICROEMULSIONS -- 4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS -- 4.1. …”
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  3. 63
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    Industrial control systems

    Published 2011
    Table of Contents: “…EXTRACTIVE FERMENTATION PROCESS FOR BIOETHANOL PRODUCTION ; 3. PLANT MODEL BASED ON ANN ; 3.1. ANN Configurations.…”
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    Mastering Scala machine learning by Kozlov, Alexander

    Published 2016
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  7. 67

    Numerical Methods for Eigenvalue Problems. by Börm, Steffen

    Published 2012
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    Comorbidity in migraine

    Published 2011
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    Building Machine Learning Systems with Python. by Richert, Willi

    Published 2013
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    Anaphora Resolution. by Mitkov, Ruslan

    Published 2014
    Table of Contents: “…4.1 Early work in anaphora resolution4.2 Student; 4.3 Shrdlu; 4.4 Lunar; 4.5 Hobbs's naïve approach; 4.5.1 The algorithm; 4.5.2 Evaluation of Hobbs' s algorithm; 4.6 The BFP algorithm; 4.7 Carter's shallow processing approach; 4.8 Rich and LuperFoy's distributed architecture; 4.9 Carbonell and Brown's multi-strategy approach; 4.10 Other work; 4.11 Summary; Chapter Five: The present: knowledge-poor and corpus-based approaches in the 1990s and beyond; 5.1 Main trends in recent anaphora resolution research; 5.2 Collocation patterns-based approach; 5.3 Lappin and Leass's algorithm; 5.3.1 Overview.…”
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    Shoulder and Elbow Arthroplasty. by Williams, Gerald R.

    Published 2004
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  20. 80

    Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs. by Karim, Rezaul

    Published 2018
    Table of Contents: “…; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.…”
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