Verdinelli Isabella (51 results)

Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

hardcover. Condition: Fine.

hardcover. Condition: Very Good.

hardcover. Condition: Very Good. In stock ready to dispatch from the UK.

Soft cover. Condition: New. Springer trade paperback, unused and carefully stored, No marks/creases or other defects; (as New). We will bubble wrap the book and ship it in a New BOX- Not a plastic bag like the zombie sellers.

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

Condition: New.

Hardback. Condition: New. This comprehensive modern look at regression covers a wide range of topics and relevant contemporary applications, going well beyond the topics covered in most introductory books. With concision and clarity, the authors present linear regression, nonparametric regression, classification, logistic and Poisson regression, high-dimensional regression, quantile regression, conformal prediction and causal inference. There are also brief introductions to neural nets, deep learning, random effects, survival analysis, graphical models and time series. Suitable for advanced undergraduate and beginning graduate students, the book will also serve as a useful reference for researchers and practitioners in data science, machine learning, and artificial intelligence who want to understand modern methods for data analysis. …

Hardback. Condition: New. This comprehensive modern look at regression covers a wide range of topics and relevant contemporary applications, going well beyond the topics covered in most introductory books. With concision and clarity, the authors present linear regression, nonparametric regression, classification, logistic and Poisson regression, high-dimensional regression, quantile regression, conformal prediction and causal inference. There are also brief introductions to neural nets, deep learning, random effects, survival analysis, graphical models and time series. Suitable for advanced undergraduate and beginning graduate students, the book will also serve as a useful reference for researchers and practitioners in data science, machine learning, and artificial intelligence who want to understand modern methods for data analysis. …

Condition: Fine. 376 pp., Paperback, spine faded, else fine. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

Condition: New. 2026. hardcover. . . . . .

paperback. Condition: Gut. 448 Seiten; 9780387986401.3 Gewicht in Gramm: 3.

Hardcover. Condition: Brand New. 1st edition. 220 pages. 6.69x0.56x9.61 inches. In Stock.

Condition: New. 2026. hardcover. . . . . . Books ship from the US and Ireland.

Condition: NEW.

Softcover. Condition: Gut. Gebraucht - Gut Zustand: Gut, Mängelexemplar, XIV, 436 p. 61 illus. About this book: The series of workshops Case Studies in Bayesian Statistics at Carnegie Mellon University is unique in devoting an entire meeting to extended presentation and discussion of scientific investigations in which statisticians play central roles within integrated, cross- disciplinary teams. The goal has been to elucidate the interplay between Bayesian theory and practice, and thereby identify successful methods and indicate important directions for future research. This volume contains the four invited case studies, with accompanying discussion, and nine contributed papers, from the 4th workshop, which was held September 27-28, 1997. While most of the case studies in this volume come from biomedical research, the reader will also find studies in environmental science and marketing research. Students and teachers of statistics, research statisticians, and investigators from other fields should find a wealth of ideas and methods in this series of case studies. Written for researchers,graduate students.…

Hardback. Condition: New. This comprehensive modern look at regression covers a wide range of topics and relevant contemporary applications, going well beyond the topics covered in most introductory books. With concision and clarity, the authors present linear regression, nonparametric regression, classification, logistic and Poisson regression, high-dimensional regression, quantile regression, conformal prediction and causal inference. There are also brief introductions to neural nets, deep learning, random effects, survival analysis, graphical models and time series. Suitable for advanced undergraduate and beginning graduate students, the book will also serve as a useful reference for researchers and practitioners in data science, machine learning, and artificial intelligence who want to understand modern methods for data analysis. …

Condition: As New. Unread book in perfect condition.

Softcover. Condition: Gut. Gebraucht - Gut Zustand: Gut, XIV, 376 p. About this book The 6th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University in October, 2001. This volume contains the invited case studies with the accompanying discussion as well as contributed papers selected by a refereeing process. Written for researchers, graduate students.…

Condition: New.

Condition: New.

Condition: New.

Condition: New. In English.

Condition: New. In English.

Condition: New. In English.

Condition: New.

Hardback. Condition: New. This comprehensive modern look at regression covers a wide range of topics and relevant contemporary applications, going well beyond the topics covered in most introductory books. With concision and clarity, the authors present linear regression, nonparametric regression, classification, logistic and Poisson regression, high-dimensional regression, quantile regression, conformal prediction and causal inference. There are also brief introductions to neural nets, deep learning, random effects, survival analysis, graphical models and time series. Suitable for advanced undergraduate and beginning graduate students, the book will also serve as a useful reference for researchers and practitioners in data science, machine learning, and artificial intelligence who want to understand modern methods for data analysis. …

Paperback. Condition: Brand New. 390 pages. 9.25x6.25x1.00 inches. In Stock.

Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.