派博傳思國(guó)際中心

標(biāo)題: Titlebook: Machine Learning; A Practical Approach Rodrigo Fernandes de Mello,Moacir Antonelli Ponti Textbook 2018 Springer International Publishing AG [打印本頁(yè)]

作者: 連續(xù)不斷 時(shí)間: 2025-3-21 18:47
書目名稱Machine Learning影響因子(影響力)

書目名稱Machine Learning影響因子(影響力)學(xué)科排名

書目名稱Machine Learning網(wǎng)絡(luò)公開(kāi)度

書目名稱Machine Learning網(wǎng)絡(luò)公開(kāi)度學(xué)科排名

書目名稱Machine Learning被引頻次

書目名稱Machine Learning被引頻次學(xué)科排名

書目名稱Machine Learning年度引用

書目名稱Machine Learning年度引用學(xué)科排名

書目名稱Machine Learning讀者反饋

書目名稱Machine Learning讀者反饋學(xué)科排名

作者: 抱負(fù) 時(shí)間: 2025-3-21 22:20

作者: PALMY 時(shí)間: 2025-3-22 02:33
A Brief Review on Machine Learning,osis of people under severe diseases, classify wine types, separate some material according to its quality (e.g. wood could be separated according to its weakness, so it could be later used to build either pencils or houses).

作者: Perineum 時(shí)間: 2025-3-22 05:28

作者: 搖擺 時(shí)間: 2025-3-22 09:26

作者: Glossy 時(shí)間: 2025-3-22 16:02

作者: Mucosa 時(shí)間: 2025-3-22 17:59

作者: 飛行員 時(shí)間: 2025-3-22 22:28
978-3-030-06949-0Springer International Publishing AG, part of Springer Nature 2018

作者: narcotic 時(shí)間: 2025-3-23 04:42
Statistical Learning Theory,l risk a good estimator for the expected risk, given the bias of some learning algorithm. This bound is the main theoretical tool to provide learning guarantees for classification tasks. Afterwards, other useful tools and concepts are introduced.

作者: 即席 時(shí)間: 2025-3-23 06:44
presents a very simple approach to understand the Statistic.This book presents the Statistical Learning Theory in a detailed and easy to understand way, by using practical examples, algorithms and source codes. It can be used as a textbook in graduation or undergraduation courses, for self-learners

作者: 后退 時(shí)間: 2025-3-23 10:15
Textbook 2018. It can be used as a textbook in graduation or undergraduation courses, for self-learners, or as reference with respect to the main theoretical concepts of Machine Learning. Fundamental concepts of Linear Algebra and Optimization applied to Machine Learning are provided, as well as source codes in

作者: 未成熟 時(shí)間: 2025-3-23 14:36
A Brief Introduction on Kernels,ace is sufficiently linearly separable. On the other hand, many input spaces are, in fact, not linearly separable. In order to overcome this restriction, nonlinear transformations can be used to implicitly obtain a more adequate space.

作者: Osteoarthritis 時(shí)間: 2025-3-23 21:38
Textbook 2018alize the Statistical Learning Theory, allowing the practical study of different classification algorithms. Then, we proceed with concentration inequalities until arriving to the Generalization and the Large-Margin bounds, providing the main motivations for the Support Vector Machines.?. From that,

作者: murmur 時(shí)間: 2025-3-24 02:00

作者: 反抗者 時(shí)間: 2025-3-24 02:40
Rodrigo Fernandes de Mello,Moacir Antonelli Pontierkmale.viele Tipps und Checklisten für die t?gliche Routine.Neu in der 7. Auflage:?.Erneuerung vieler Einstellungs- und R?ntgenaufnahmen an modernsten Ger?ten..ausführliche Darstellung digitaler Techniken in d978-3-662-56256-7

作者: MOCK 時(shí)間: 2025-3-24 08:56
Rodrigo Fernandes de Mello,Moacir Antonelli Pontierkmale.viele Tipps und Checklisten für die t?gliche Routine.Neu in der 7. Auflage:?.Erneuerung vieler Einstellungs- und R?ntgenaufnahmen an modernsten Ger?ten..ausführliche Darstellung digitaler Techniken in d978-3-662-56256-7

作者: 投射 時(shí)間: 2025-3-24 13:03
ation algorithms. Then, we proceed with concentration inequalities until arriving to the Generalization and the Large-Margin bounds, providing the main motivations for the Support Vector Machines.?. From that, 978-3-030-06949-0978-3-319-94989-5

作者: engender 時(shí)間: 2025-3-24 17:28
A Brief Review on Machine Learning,osis of people under severe diseases, classify wine types, separate some material according to its quality (e.g. wood could be separated according to its weakness, so it could be later used to build either pencils or houses).

作者: 騷動(dòng) 時(shí)間: 2025-3-24 19:37
Statistical Learning Theory,zation (ERM) principle, which is the key point for the Statistical Learning Theory (SLT). The ERM principle provides upper bounds to make the empirical risk a good estimator for the expected risk, given the bias of some learning algorithm. This bound is the main theoretical tool to provide learning

作者: Longitude 時(shí)間: 2025-3-24 23:09
Introduction to Support Vector Machines,vides an intuitive and an algebraic formulation to obtain the optimization problem of the Support Vector Machines. At last, hard-margin and soft-margin SVMs are detailed, including the necessary mathematical tools to tackle them both.

作者: nostrum 時(shí)間: 2025-3-25 03:56
A Brief Introduction on Kernels, the loss via margin maximization. This maximization led to a dual optimization problem resulting in a Lagrangian function which is quadratic and requires simple inequality constraints. The support vectors are responsible for defining the hyperplane, resulting in the support vector classifier . whic

作者: omnibus 時(shí)間: 2025-3-25 07:55