Isbn: 9781032358260 - applications of machine learning and deep learning on biological data (13 risultati)

Applications of Machine Learning and Deep Learning on Biological Data
Masoodi, Faheem (EDT); Quasim, Mohammad (EDT); Bukhari, Syed (EDT); Dixit, Sarvottam (EDT); Alam, Shadab (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Applications of Machine Learning and Deep Learning on Biological Data
Masoodi, Faheem (EDT); Quasim, Mohammad (EDT); Bukhari, Syed (EDT); Dixit, Sarvottam (EDT); Alam, Shadab (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: California Books, Miami, FL, U.S.A.California Books
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Applications of Machine Learning and Deep Learning on Biological Data
Masoodi, Faheem (EDT); Quasim, Mohammad (EDT); Bukhari, Syed (EDT); Dixit, Sarvottam (EDT); Alam, Shadab (EDT)
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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Paperback. Condizione: New. The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, comprehensive programming of bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and efficacy of programming such algorithms.Applications of Machine Learning and Deep Learning on Biological Data is an examination of applying ML and DL to such areas as proteomics, genomics, microarrays, text mining, and systems biology. The key objective is to cover ML applications to biological science problems, focusing on problems related to bioinformatics. The book looks at cutting-edge research topics and methodologies in ML applied to the rapidly advancing discipline of bioinformatics. ML and DL applied to biological and neuroimaging data can open new frontiers for biomedical engineering, such as refining the understanding of complex diseases, including cancer and neurodegenerative and psychiatric disorders. Advances in this field could eventually lead to the development of precision medicine and automated diagnostic tools capable of tailoring medical treatments to individual lifestyles, variability, and the environment.Highlights include:Artificial Intelligence in treating and diagnosing schizophreniaAn analysis of ML's and DL's financial effect on healthcareAn XGBoost-based classification method for breast cancer classificationUsing ML to predict squamous diseasesML and DL applications in genomics and proteomicsApplying ML and DL to biological data.…

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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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Applications of Machine Learning and Deep Learning on Biological Data
Masoodi, Faheem (EDT); Quasim, Mohammad (EDT); Bukhari, Syed (EDT); Dixit, Sarvottam (EDT); Alam, Shadab (EDT)
- Brossura
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Condizione: New. In English.

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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 210 pages. 9.18x6.12x9.21 inches. In Stock.

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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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EUR 78,30
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Paperback. Condizione: New. The automated learning of machines characterizes machine learning (ML). It focuses on making data-driven predictions using programmed algorithms. ML has several applications, including bioinformatics, which is a discipline of study and practice that deals with applying computational derivations to obtain biological data. It involves the collection, retrieval, storage, manipulation, and modeling of data for analysis or prediction made using customized software. Previously, comprehensive programming of bioinformatical algorithms was an extremely laborious task for such applications as predicting protein structures. Now, algorithms using ML and deep learning (DL) have increased the speed and efficacy of programming such algorithms.Applications of Machine Learning and Deep Learning on Biological Data is an examination of applying ML and DL to such areas as proteomics, genomics, microarrays, text mining, and systems biology. The key objective is to cover ML applications to biological science problems, focusing on problems related to bioinformatics. The book looks at cutting-edge research topics and methodologies in ML applied to the rapidly advancing discipline of bioinformatics. ML and DL applied to biological and neuroimaging data can open new frontiers for biomedical engineering, such as refining the understanding of complex diseases, including cancer and neurodegenerative and psychiatric disorders. Advances in this field could eventually lead to the development of precision medicine and automated diagnostic tools capable of tailoring medical treatments to individual lifestyles, variability, and the environment.Highlights include:Artificial Intelligence in treating and diagnosing schizophreniaAn analysis of ML's and DL's financial effect on healthcareAn XGBoost-based classification method for breast cancer classificationUsing ML to predict squamous diseasesML and DL applications in genomics and proteomicsApplying ML and DL to biological data.…

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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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paperback. Condizione: New. New .Ships From Multiple Locations. book.

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- Print on Demand
Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

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- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides readers a comprehensive understanding of the application of machine Learning and deep Learning in proteomics, genomics, microarrays, text mining and related fields. The key objective is to provide machine learning applications to biological science problems, focusing on problems related to bioinformatics.…