ISBN: 9786138914723 - Exercising Machine Language Paradigms in Software Engineering: A Quick Primer (8 results)

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  • Language: English

    Published by Scholars' Press, 2019

    6138914724 / 9786138914723

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  • Language: English

    Published by Scholars\' Press, 2019

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  • Language: English

    Published by Scholars' Press, 2019

    6138914724 / 9786138914723

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    Taschenbuch. Condition: Neu. Exercising machine language paradigms in software engineering | A Quick Primer | Manas Kumar Yogi (u. a.) | Taschenbuch | 52 S. | Englisch | 2019 | Scholars' Press | EAN 9786138914723 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

  • Language: English

    Published by Scholars' Press Okt 2019, 2019

    6138914724 / 9786138914723

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Precise estimation of software development exertion is basic in software designing. Thinks little of lead to time weights that may bargain full useful development and intensive testing of software. Interestingly, overestimates can bring about noncompetitive contract offers as well as over designation of development assets and work force. Thus, numerous models for assessing software development exertion have been proposed. This work portrays principles of machine learning, which we use to manufacture estimators of software development exertion from recorded information. Our work demonstrates that these strategies are focused with conventional estimators on one dataset, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This preventative note applies to any model-development procedure that depends on authentic information. Every single such model for software exertion estimation ought to be assessed by investigating model affectability on an assortment of authentic information. 52 pp. Englisch. …

  • Language: English

    Published by Scholars' Press, 2019

    6138914724 / 9786138914723

    • Softcover
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  • Language: English

    Published by Scholars' Press, 2019

    6138914724 / 9786138914723

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  • Language: English

    Published by Scholars' Press, 2019

    6138914724 / 9786138914723

    • Softcover
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    Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Precise estimation of software development exertion is basic in software designing. Thinks little of lead to time weights that may bargain full useful development and intensive testing of software. Interestingly, overestimates can bring about noncompetitive contract offers as well as over designation of development assets and work force. Thus, numerous models for assessing software development exertion have been proposed. This work portrays principles of machine learning, which we use to manufacture estimators of software development exertion from recorded information. Our work demonstrates that these strategies are focused with conventional estimators on one dataset, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This preventative note applies to any model-development procedure that depends on authentic information. Every single such model for software exertion estimation ought to be assessed by investigating model affectability on an assortment of authentic information. …

  • Language: English

    Published by Scholars' Press Okt 2019, 2019

    6138914724 / 9786138914723

    • Softcover
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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Precise estimation of software development exertion is basic in software designing. Thinks little of lead to time weights that may bargain full useful development and intensive testing of software. Interestingly, overestimates can bring about noncompetitive contract offers as well as over designation of development assets and work force. Thus, numerous models for assessing software development exertion have been proposed. This work portrays principles of machine learning, which we use to manufacture estimators of software development exertion from recorded information. Our work demonstrates that these strategies are focused with conventional estimators on one dataset, yet additionally delineate that these techniques are delicate to the information on which they are prepared. This preventative note applies to any model-development procedure that depends on authentic information. Every single such model for software exertion estimation ought to be assessed by investigating model affectability on an assortment of authentic information.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. …