Isbn: 9789999335102 - Mental Health Analysis Based on Machine Learning (10 results)

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  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

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    Seller: California Books, Miami, FL, U.S.A.California Books

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  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

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    Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

    • Softcover

    Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK

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    PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

    • Softcover

    Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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    Paperback. Condition: Brand New. 153 pages. 6.00x0.35x9.00 inches. In Stock.

  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

    • Softcover

    Seller: Books Puddle, New York, NY, U.S.A.Books Puddle

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  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

    • Softcover
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    Seller: Majestic Books, Hounslow, United KingdomMajestic Books

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  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

    • Softcover
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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

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    Paperback. Condition: new. Paperback. Mental health illness prediction system using machine learning algorithms focuses on the use of artificial intelligence techniques to support early detection of mental health conditions. Here, students are considered as target population. This book explores how machine learning algorithms can be effectively applied to predictive models of mental health illnesses to predict any kind of disorder among students so that early precaution can be taken. It presents a structured framework for designing and implementing an intelligent prediction system based on machine learning, covering data preparation includes data collection, data preprocessing, feature extraction, algorithm selection techniques for model development, training, testing, and system deployment, performance analysis. In addition to theoretical insights, the book presents real-world case studies that illustrate the deployment of predictive models in mental health applications. It highlights various machine learning algorithms and their role in improving prediction accuracy and decision support. The content addresses real-world challenges for students, developers, and healthcare researchers and professional audiences, the book bridges the gap between mental health studies and intelligent computing technologies. It supports early diagnosis and decision-making in mental health care. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

    • Softcover
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    Seller: preigu, Osnabrück, Germanypreigu

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    Taschenbuch. Condition: Neu. Mental Health Analysis based on Machine Learning | Priyanka Mangal | Taschenbuch | Englisch | 2026 | Eliva Press | EAN 9789999335102 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

  • Language: English

    Published by Eliva Press, 2026

    9999335101 / 9789999335102

    • Softcover
    • Print on Demand

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mental health illness prediction system using machine learning algorithms focuses on the use of artificial intelligence techniques to support early detection of mental health conditions. Here, students are considered as target population. This book explores how machine learning algorithms can be effectively applied to predictive models of mental health illnesses to predict any kind of disorder among students so that early precaution can be taken. It presents a structured framework for designing and implementing an intelligent prediction system based on machine learning, covering data preparation includes data collection, data preprocessing, feature extraction, algorithm selection techniques for model development, training, testing, and system deployment, performance analysis.In addition to theoretical insights, the book presents real-world case studies that illustrate the deployment of predictive models in mental health applications. It highlights various machine learning algorithms and their role in improving prediction accuracy and decision support. The content addresses real-world challenges for students, developers, and healthcare researchers and professional audiences, the book bridges the gap between mental health studies and intelligent computing technologies. It supports early diagnosis and decision-making in mental health care.