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001
000005123365
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20230302101512
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230203s2020 us a b 001c0 eng
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▼a 2019040762
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015
▼a GBC022925
▼2 bnb -
020
▼a 9781108470049
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035
▼a (KERIS)REF000019428058
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040
▼a LBSOR/DLC
▼b eng
▼c DLC
▼d OCLCO
▼d UKMGB
▼d YDX
▼d 211070 -
042
▼a pcc
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050
▼a Q325.5
-
090
▼a Q325.5
▼b D325 -
245
▼a Mathematics for machine learning /
▼d Marc Peter Deisenroth,
▼e A. Aldo Faisal,
▼e Cheng Soon Ong -
260
▼a Cambridge, United Kingdom ;
▼a New York, NY :
▼b Cambridge University Press,
▼c 2020 -
300
▼a 371 p. :
▼b ill. ;
▼c 26 cm -
504
▼a Includes bibliographical references and index
-
505
▼a Introduction and motivation -- Linear algebra -- Analytic geometry -- Matrix decompositions -- Vector calculus -- Probability and distribution -- Continuous optimization -- When models meet data -- Linear regression -- Dimensionality reduction with principal component analysis -- Density estimation with Gaussian mixture models -- Classification with support vector machines.
-
520
▼a "The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability, and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models, and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts"--
▼c Provided by publisher -
650
▼a Machine learning
▼x Mathematics -
700
▼a Deisenroth, Marc Peter,
▼e author -
700
▼a Faisal, A. Aldo,
▼e author -
700
▼a Ong, Cheng Soon,
▼e author -
950
▼b 영국74.99
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상세정보
Mathematics for machine learning
QR코드| 자료유형 : | 단행본 |
|---|---|
| ISBN : | 9781108470049 |
| 분류기호 : | Q325.5 |
| 서명/저자사항 : | Mathematics for machine learning / Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong |
| 발행사항 : | Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2020 |
| 형태사항 : | 371 p. : ill. ; 26 cm |
| 서지주기 : | Includes bibliographical references and index |
| 내용주기 : | Introduction and motivation -- Linear algebra -- Analytic geometry -- Matrix decompositions -- Vector calculus -- Probability and distribution -- Continuous optimization -- When models meet data -- Linear regression -- Dimensionality reduction with principal component analysis -- Density estimation with Gaussian mixture models -- Classification with support vector machines. |
| 요약 : | "The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability, and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models, and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts"-- Provided by publisher |
| 일반주제명 : | Machine learning -- Mathematics -- |
| 개인저자 : | Deisenroth, Marc Peter, author |
| 개인저자 : | Faisal, A. Aldo, author |
| 개인저자 : | Ong, Cheng Soon, author |
| 언어 | 영어 |
예약
- 1. 예약현황은 홈페이지 로그인 후 예약 페이지에 확인 가능합니다.
- 2. 도착 통보된 예약자료 대출을 원하지 않는 경우에는 예약 현황에서 취소할 수 있습니다.
- 3. 기타 문의사항은 도서관에 문의 바랍니다.
무인예약대출
- 1. 무인예약대출 현황은 홈페이지 로그인 후 무인예약대출 페이지에 확인 가능합니다.
- 2. 무인예약대출자료 대출을 원하지 않는 경우에는 무인예약대출 페이지에서 신청 또는 접수상태인 경우만 취소할 수 있습니다.
- 3. 희망대출일은 신청일로부터 최대 1주일 까지 가능합니다.
- 4. 희망대출일을 선택하지 않은 경우 대출대기 통보 후 1주일까지 기기에서 대출가능합니다.
- 5. 기타 문의사항은 도서관에 문의 바랍니다.
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