![[고정]교보 e캐시 더드림](https://simage.kyobobook.co.kr/dwas/images/prom/banner/2019/12/30/bnS_pc_ink_83x118.jpg)
| ISBN | 9780262046824(0262046822) |
|---|---|
| 쪽수 | 864쪽 |
| 언어 | English |
| 크기 | 208(W) X 236(H) X 39(T) (mm) |
| 제본형태 | Hardcover |
| 총권수 | 1권 |
책소개
이 책이 속한 분야
이 책의 설명
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.
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.
목차
1 Introduction 1
I Foundations 29
2 Probability: Univariate Models 31
3 Probability: Multivariate Models 75
4 statistics 103
5 Decision Theory 163
6 Information Theory 199
7 Linear Algebra 221
8 Optimization 269
II Linear Models 315
9 Linear Discriminant Analysis 317
10 Logistic Regression 333
11 Linear Regression 365
12 Generalized Linear Models * 409
III Deep Neural Networks 417
13 Neural Networks for Structured Data 419
14 Neural Networks for Images 461
15 Neural Networks for Sequences 497
IV Nonparametric Models 539
16 Exemplar-based Methods 541
17 Kernel Methods * 561
18 Trees, Forests, Bagging, and Boosting 597
V Beyond Supervised Learning 619
19 Learning with Fewer Labeled Examples 621
20 Dimensionality Reduction 651
21 Clustering 709
22 Recommender Systems 735
23 Graph Embeddings * 747
A Notation 767
I Foundations 29
2 Probability: Univariate Models 31
3 Probability: Multivariate Models 75
4 statistics 103
5 Decision Theory 163
6 Information Theory 199
7 Linear Algebra 221
8 Optimization 269
II Linear Models 315
9 Linear Discriminant Analysis 317
10 Logistic Regression 333
11 Linear Regression 365
12 Generalized Linear Models * 409
III Deep Neural Networks 417
13 Neural Networks for Structured Data 419
14 Neural Networks for Images 461
15 Neural Networks for Sequences 497
IV Nonparametric Models 539
16 Exemplar-based Methods 541
17 Kernel Methods * 561
18 Trees, Forests, Bagging, and Boosting 597
V Beyond Supervised Learning 619
19 Learning with Fewer Labeled Examples 621
20 Dimensionality Reduction 651
21 Clustering 709
22 Recommender Systems 735
23 Graph Embeddings * 747
A Notation 767
출판사 서평
“The deep learning revolution has transformed the field of machine learning over the last decade. It was inspired by attempts to mimic the way the brain learns but it is grounded in basic principles of statistics, information theory, decision theory, and optimization. This book does an excellent job...
더보기
Klover 리뷰 (0)
북로그 리뷰 (0) 쓰러가기
북로그 리뷰는 본인 인증 후 작성 가능합니다.
책이나 타인에 대해 근거 없이 비방을 하거나 타인의 명예를 훼손할 수 있는 내용은 비공개 처리 될 수 있습니다.
※ 북로그 리뷰 리워드 제공 2021. 4. 1 종료
책이나 타인에 대해 근거 없이 비방을 하거나 타인의 명예를 훼손할 수 있는 내용은 비공개 처리 될 수 있습니다.
※ 북로그 리뷰 리워드 제공 2021. 4. 1 종료
문장수집 (0) 문장수집 쓰기 나의 독서기록 보기
※구매 후 문장수집 작성 시, 리워드를 제공합니다.
안내
교환/반품/품절안내
※ 상품 설명에 반품/교환 관련한 안내가 있는 경우 그 내용을 우선으로 합니다. (업체 사정에 따라 달라질 수 있습니다.)
| 반품/교환방법 | 마이룸 > 주문관리 > 주문/배송내역 > 주문조회 > 반품/교환신청 , [1:1상담>반품/교환/환불] 또는 고객센터 (1544-1900) ※ 오픈마켓, 해외배송주문, 기프트 주문시 [1:1상담>반품/교환/환불] 또는 고객센터 (1544-1900) |
|---|---|
| 반품/교환가능 기간 | 변심반품의 경우 수령 후 7일 이내, 상품의 결함 및 계약내용과 다를 경우 문제점 발견 후 30일 이내 |
| 반품/교환비용 | 변심 혹은 구매착오로 인한 반품/교환은 반송료 고객 부담 |
| 반품/교환 불가 사유 |
|
| 상품 품절 | 공급사(출판사) 재고 사정에 의해 품절/지연될 수 있으며, 품절 시 관련 사항에 대해서는 이메일과 문자로 안내드리겠습니다. |
| 소비자 피해보상 환불지연에 따른 배상 |
|
기프트 BEST
![[동원] 동원샘물 웨이크업뷰티 500ml*20병](http://image.kyobobook.co.kr/newimages/giftshop_new/goods/400/1178/hot1655873224720.png)
![[소싱] 제로 신발 건조기](http://image.kyobobook.co.kr/newimages/giftshop_new/goods/400/1855/hot1592978996783.jpg)
![[보유]C Programming](http://image.kyobobook.co.kr/images/book/medium/503/m9780393979503.jpg)
![[보유]Deep Learning with PyTorch Lightning](http://image.kyobobook.co.kr/images/book/medium/618/m9781800561618.jpg)
![[보유]Master Algorithm](http://image.kyobobook.co.kr/images/book/medium/243/m9780141979243.jpg)
![[보유]Deep Learning](http://image.kyobobook.co.kr/images/book/medium/613/m9780262035613.jpg)
![[보유]Reinforcement Learning](http://image.kyobobook.co.kr/images/book/medium/246/m9780262039246.jpg)
![[보유]Kotlin Design Patterns and Best Practices - Second Edition](http://image.kyobobook.co.kr/images/book/medium/727/m9781801815727.jpg)
![[보유]Digital Logic](http://image.kyobobook.co.kr/images/book/medium/638/m9781119621638.jpg)
![[보유]Introduction to Classical and Quantum Computing](http://image.kyobobook.co.kr/images/book/medium/105/m9798985593105.jpg)
![[보유]The Machine Learning Solutions Architect Handbook(Paperback)](http://image.kyobobook.co.kr/images/book/medium/168/m9781801072168.jpg)
LG U+ 구매안전서비스
▶서비스 가입 확인
고객님은 안전거래를 위해 현금 등으로 결제시 저희 쇼핑몰에서 가입한 LG유플러스의 구매안전서비스를 이용하실 수 있습니다.
정보보호관리체계
ISMS 인증획득
ISMS 인증획득
[인증범위] 온라인 교보문고 서비스 운영
[유효기간] 2020.11.04. ~ 2023.11.03.
바로가기
