Kenichiro ishii (27 resultados)
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Hardcover. Condición: new. Hardcover. This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to foll…ow.Many excellent books in this field have been published in the past. However, these books are not necessarily intended for self-study by beginners.This book limits the topics to the minimum essential themes that beginners should learn, and explains them in detail. This book focuses on supervised learning, first introducing classical but important methods that have contributed to the development of the field. It then explains various methods that have since attracted attention. In explaining these methods, the book also provides a historical account of how new technologies were created as a result of combining classical ideas. The book emphasizes that Bayes decision rule is a fundamental concept in PR and ML.The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. (2) To deepen the reader's understanding, exercises are provided at the end of each chapter with detailed solutions available online.(3) To promote the reader's intuitive understanding, the book presents as many concrete examples as possible.(4) Coffee Break columns introduce knowledge and know-how from the author's experience. Unsupervised learning will be discussed in a sequel. mso-fareast-language: EN-US;">The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning
Ishii, Kenichiro (Author)/ Ueda, Naonori (Author)/ Maeda, Eisaku (Author)/ Murase, Hiroshi (Author)
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Hardcover. Condición: Brand New. 479 pages. 9.26x6.11x1.10 inches. In Stock.
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Hardcover. Condición: new. Hardcover. This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to foll…ow.Many excellent books in this field have been published in the past. However, these books are not necessarily intended for self-study by beginners.This book limits the topics to the minimum essential themes that beginners should learn, and explains them in detail. This book focuses on supervised learning, first introducing classical but important methods that have contributed to the development of the field. It then explains various methods that have since attracted attention. In explaining these methods, the book also provides a historical account of how new technologies were created as a result of combining classical ideas. The book emphasizes that Bayes decision rule is a fundamental concept in PR and ML.The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. (2) To deepen the reader's understanding, exercises are provided at the end of each chapter with detailed solutions available online.(3) To promote the reader's intuitive understanding, the book presents as many concrete examples as possible.(4) Coffee Break columns introduce knowledge and know-how from the author's experience. Unsupervised learning will be discussed in a sequel. mso-fareast-language: EN-US;">The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning (Springer Asia Pacific Mathematics Series, 1)
Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi
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Paperback. Condición: New.
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Hardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Hardcover. Condición: new. Hardcover. This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to foll…ow.Many excellent books in this field have been published in the past. However, these books are not necessarily intended for self-study by beginners.This book limits the topics to the minimum essential themes that beginners should learn, and explains them in detail. This book focuses on supervised learning, first introducing classical but important methods that have contributed to the development of the field. It then explains various methods that have since attracted attention. In explaining these methods, the book also provides a historical account of how new technologies were created as a result of combining classical ideas. The book emphasizes that Bayes decision rule is a fundamental concept in PR and ML.The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. (2) To deepen the reader's understanding, exercises are provided at the end of each chapter with detailed solutions available online.(3) To promote the reader's intuitive understanding, the book presents as many concrete examples as possible.(4) Coffee Break columns introduce knowledge and know-how from the author's experience. Unsupervised learning will be discussed in a sequel. mso-fareast-language: EN-US;">The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Pattern Recognition and Machine Learning for Self-Study I
Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnThe number of males diagnosed with prostate cancer (PCa) is increasing all over the world. Most patients with early-stage PCa can be treated with appropriate therapy, such as radical prostatectomy or ir…radiation. On the other hand.
Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning (Springer Asia Pacific Mathematics Series, 1)
Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The number of males diagnosed with prostate cancer (PCa) is increasing all over the world. Most patients with early-stage PCa can be treated with appropriate therapy, such as radical prostatectomy or irradiation. On the other hand, androgen dep…rivation therapy (ADT) is the standard systemic therapy given to patients with advanced PCa. ADT induces temporary remission, but the majority of patients (approximately 60%) eventually progress to castration-resistant prostate cancer (CRPC), which is associated with a high mortality rate. Generally, well-differentiated PCa cells are androgen dependent, i.e., androgen receptor (AR) signalling regulates cell cycle and differentiation. The loss of AR signalling after ADT triggers androgen-independent outgrowth, generating poorly differentiated, uncontrollable PCa cells. Once PCa cells lose their sensitivity to ADT, effective therapies are limited. In the last few years, however, several new options for the treatment of CRPC have been approved, e.g., the CYP17 inhibitor, the AR antagonist, and the taxane. Despite this progress in the development of new drugs, there is a high medical need for optimizing the sequence and combination of approved drugs. Thus, the identification of predictive biomarkers may help in the context of personalized medicine to guide treatment decisions, improve clinical outcomes, and prevent unnecessary side effects. In this Special Issue Book, we focused on the cytobiology of human PCa cells and its clinical applications to develop a major step towards personalized medicine matched to the individual needs of patients with early-stage and advanced PCa and CRPC. We hope that this Special Issue Book attracts the attention of readers with expertise and interest in the cytobiology of PCa cells.
Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning (Springer Asia Pacific Mathematics Series, 1)
Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi
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Buch. Condición: Neu. Pattern Recognition and Machine Learning for Self-Study I | Supervised Learning | Kenichiro Ishii (u. a.) | Buch | Springer Asia Pacific Mathematics Series | xx | Englisch | 2026 | Springer | EAN 9789819514779 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, ju…ergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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Buch. Condición: Neu. Cytobiology of Human Prostate Cancer Cells and Its Clinical Applications | Buch | Gebunden | Englisch | 2020 | MDPI AG | EAN 9783039360345 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
