Author: Mahathi Narayanaswamy
Publisher: Chennai Young Naturalists' Network
ISBN:
Category : Fiction
Languages : en
Pages : 42
Book Description
A free e-Magazine written and published by Young Naturalists' based in Chennai.
Nature Trail Vol.2 Ed.2
Author: Mahathi Narayanaswamy
Publisher: Chennai Young Naturalists' Network
ISBN:
Category : Fiction
Languages : en
Pages : 42
Book Description
A free e-Magazine written and published by Young Naturalists' based in Chennai.
Publisher: Chennai Young Naturalists' Network
ISBN:
Category : Fiction
Languages : en
Pages : 42
Book Description
A free e-Magazine written and published by Young Naturalists' based in Chennai.
The Elements of Statistical Learning
Author: Trevor Hastie
Publisher: Springer Science & Business Media
ISBN: 0387216065
Category : Mathematics
Languages : en
Pages : 545
Book Description
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Publisher: Springer Science & Business Media
ISBN: 0387216065
Category : Mathematics
Languages : en
Pages : 545
Book Description
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
British Moralists
Author: Sir Lewis Amherst Selby-Bigge
Publisher:
ISBN:
Category : Ethics
Languages : en
Pages : 508
Book Description
Publisher:
ISBN:
Category : Ethics
Languages : en
Pages : 508
Book Description
The Principles of Ethics
Author: Herbert Spencer
Publisher:
ISBN:
Category : Ethics
Languages : en
Pages : 594
Book Description
Publisher:
ISBN:
Category : Ethics
Languages : en
Pages : 594
Book Description
The History of English Law Before the Time of Edward I.
Author: Frederick Pollock
Publisher:
ISBN:
Category : Law
Languages : en
Pages : 738
Book Description
Publisher:
ISBN:
Category : Law
Languages : en
Pages : 738
Book Description
Probabilistic Machine Learning
Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
Book Description
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
Book Description
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Proceedings of the Boston Society of Natural History
Author: Boston Society of Natural History
Publisher:
ISBN:
Category : Natural history
Languages : en
Pages : 980
Book Description
Publisher:
ISBN:
Category : Natural history
Languages : en
Pages : 980
Book Description
Refactoring
Author: Martin Fowler
Publisher: Addison-Wesley Professional
ISBN: 0201485672
Category : Computers
Languages : en
Pages : 461
Book Description
Refactoring is gaining momentum amongst the object oriented programming community. It can transform the internal dynamics of applications and has the capacity to transform bad code into good code. This book offers an introduction to refactoring.
Publisher: Addison-Wesley Professional
ISBN: 0201485672
Category : Computers
Languages : en
Pages : 461
Book Description
Refactoring is gaining momentum amongst the object oriented programming community. It can transform the internal dynamics of applications and has the capacity to transform bad code into good code. This book offers an introduction to refactoring.
Handbook of Enology, Volume 1
Author: Pascal Ribéreau-Gayon
Publisher: John Wiley & Sons
ISBN: 0470010355
Category : Science
Languages : en
Pages : 512
Book Description
The "Microbiology" volume of the new revised and updated Handbook of Enology focuses on the vinification process. It describes how yeasts work and how they can be influenced to achieve better results. It continues to look at the metabolism of lactic acid bacterias and of acetic acid bacterias, and again, how can they be treated to avoid disasters in the winemaking process and how to achieve optimal results. The last chapters in the book deal with the use of sulfur-dioxide, the grape and its maturation process, harvest and pre-fermentation treatment, and the basis of red, white and speciality wine making. The result is the ultimate text and reference on the science and technology of the vinification process: understanding and dealing with yeasts and bacterias involved in the transformation from grape to wine. A must for all serious students and practitioners involved in winemaking.
Publisher: John Wiley & Sons
ISBN: 0470010355
Category : Science
Languages : en
Pages : 512
Book Description
The "Microbiology" volume of the new revised and updated Handbook of Enology focuses on the vinification process. It describes how yeasts work and how they can be influenced to achieve better results. It continues to look at the metabolism of lactic acid bacterias and of acetic acid bacterias, and again, how can they be treated to avoid disasters in the winemaking process and how to achieve optimal results. The last chapters in the book deal with the use of sulfur-dioxide, the grape and its maturation process, harvest and pre-fermentation treatment, and the basis of red, white and speciality wine making. The result is the ultimate text and reference on the science and technology of the vinification process: understanding and dealing with yeasts and bacterias involved in the transformation from grape to wine. A must for all serious students and practitioners involved in winemaking.
Clinical biochemistry. Principles and methods. Vol. 2
Author: H. C. Curtius
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3111433994
Category : Medical
Languages : en
Pages : 912
Book Description
No detailed description available for "CLINICAL BIOCHEMISTRY (CURTIUS) V. 2 CBPM E-BOOK".
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3111433994
Category : Medical
Languages : en
Pages : 912
Book Description
No detailed description available for "CLINICAL BIOCHEMISTRY (CURTIUS) V. 2 CBPM E-BOOK".