Isbn: 9798906434180 - introduction to machine learning in pharmaceutical sciences (6 resultados)

ISBN: 
Refinar con la Búsqueda avanzada

Filtrar la búsqueda

  • Libros (6)

  • Nuevo (6)

a

Intervalo de precios personalizado (EUR)

a

  • Idioma: Inglés

    Editorial: Notion Press, 2026

    9798906434180

    • Tapa blanda

    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 33,61

     Gastos de envío gratis 
    Se envía dentro de Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: Notion Press Media Pvt. Ltd, 2026

    9798906434180

    • Tapa blanda

    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 31,09

    Envío por EUR 4,85 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

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

  • Idioma: Inglés

    Editorial: Notion Press, 2026

    9798906434180

    • Tapa blanda
    • Impresión bajo demanda

    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 35,43

    Envío por EUR 43,16 
    Se envía de Reino Unido a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. Pharmaceutical science is entering a new era in which data can reveal patterns, predict outcomes, and guide decisions that conventional analysis may overlook. Introduction to Machine Learning in Pharmaceutical Sciences provides a clear and practical pathway into this rapidly evolving field, connecting computational principles with real pharmaceutical challenges.Beginning with the foundations of artificial intelligence, machine learning, and data science, the book explains pharmaceutical datasets, data preparation, regression, classification, clustering, decision trees, and model evaluation in an accessible yet scientifically rigorous manner. Application-focused discussions demonstrate how these methods support drug discovery, formulation development, quality control, manufacturing, pharmacovigilance, and clinical decision-making.Designed for pharmacy students, teachers, researchers, and early-career pharmaceutical professionals, the book bridges the gap between theoretical algorithms and their responsible use in pharmaceutical research and healthcare. Readers gain the conceptual foundation needed to interpret models critically, assess the reliability of predictions, and convert complex data into meaningful scientific insight.For anyone seeking to understand how machine learning is reshaping pharmaceutical sciences, this book offers an authoritative and accessible starting point. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Notion Press, 2026

    9798906434180

    • Tapa blanda
    • Impresión bajo demanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 46,43

    Envío por EUR 35,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Pharmaceutical science is entering a new era in which data can reveal patterns, predict outcomes, and guide decisions that conventional analysis may overlook. Introduction to Machine Learning in Pharmaceutical Sciences provides a clear and practical pathway into this rapidly evolving field, connecting computational principles with real pharmaceutical challenges.Beginning with the foundations of artificial intelligence, machine learning, and data science, the book explains pharmaceutical datasets, data preparation, regression, classification, clustering, decision trees, and model evaluation in an accessible yet scientifically rigorous manner. Application-focused discussions demonstrate how these methods support drug discovery, formulation development, quality control, manufacturing, pharmacovigilance, and clinical decision-making.Designed for pharmacy students, teachers, researchers, and early-career pharmaceutical professionals, the book bridges the gap between theoretical algorithms and their responsible use in pharmaceutical research and healthcare. Readers gain the conceptual foundation needed to interpret models critically, assess the reliability of predictions, and convert complex data into meaningful scientific insight.For anyone seeking to understand how machine learning is reshaping pharmaceutical sciences, this book offers an authoritative and accessible starting point.…

  • Idioma: Inglés

    Editorial: Notion Press, 2026

    9798906434180

    • Tapa blanda
    • Impresión bajo demanda

    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 50,94

    Envío por EUR 32,63 
    Se envía de Australia a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. Pharmaceutical science is entering a new era in which data can reveal patterns, predict outcomes, and guide decisions that conventional analysis may overlook. Introduction to Machine Learning in Pharmaceutical Sciences provides a clear and practical pathway into this rapidly evolving field, connecting computational principles with real pharmaceutical challenges.Beginning with the foundations of artificial intelligence, machine learning, and data science, the book explains pharmaceutical datasets, data preparation, regression, classification, clustering, decision trees, and model evaluation in an accessible yet scientifically rigorous manner. Application-focused discussions demonstrate how these methods support drug discovery, formulation development, quality control, manufacturing, pharmacovigilance, and clinical decision-making.Designed for pharmacy students, teachers, researchers, and early-career pharmaceutical professionals, the book bridges the gap between theoretical algorithms and their responsible use in pharmaceutical research and healthcare. Readers gain the conceptual foundation needed to interpret models critically, assess the reliability of predictions, and convert complex data into meaningful scientific insight.For anyone seeking to understand how machine learning is reshaping pharmaceutical sciences, this book offers an authoritative and accessible starting point. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Notion Press, 2026

    9798906434180

    • Tapa blanda
    • Impresión bajo demanda

    Librería: preigu, Osnabrück, Alemaniapreigu

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 47,35

    Envío por EUR 70,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Introduction to Machine Learning in Pharmaceutical Sciences | Shrey Dahiya (u. a.) | Taschenbuch | Englisch | 2026 | Notion Press | EAN 9798906434180 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …