소장자료
| LDR | 02695cam a2200000 a | ||
| 001 | 0100876201▲ | ||
| 005 | 20250811113452▲ | ||
| 007 | ta ▲ | ||
| 008 | 220506s20202021caua 001 0 eng c▲ | ||
| 020 | ▼a1492073059▲ | ||
| 020 | ▼a9781492073055▼q(pbk.)▲ | ||
| 035 | ▼a(KERIS)REF000020029114▲ | ||
| 040 | ▼aYDX▼beng▼cYDX▼dBDX▼dJRZ▼dOCLCO▼dOCLCF▼dUOK▼dOCLCO▼dRUSOM▼dOCLCQ▼dDLC▼d221016▲ | ||
| 082 | 0 | 4 | ▼a006.31▼223▲ |
| 090 | ▼a006.31▼bT219m▲ | ||
| 100 | 1 | ▼aTatsat, Hariom.▲ | |
| 245 | 1 | 0 | ▼aMachine learning and data science blueprints for finance :▼bfrom building trading strategies to robo-advisors using Python /▼cby Hariom Tatsat, Sahil Puri, Brad Lookabaugh.▲ |
| 260 | ▼aSebastopol, CA :▼bO'Reilly Media,▼c2020.▲ | ||
| 300 | ▼axv, 409 p. :▼bill. ;▼c24 cm▲ | ||
| 336 | ▼atext▼btxt▼2rdacontent▲ | ||
| 337 | ▼aunmediated▼bn▼2rdamedia▲ | ||
| 338 | ▼avolume▼bnc▼2rdacarrier▲ | ||
| 500 | ▼aIncludes index.▲ | ||
| 505 | 0 | ▼aPart 1. The framework. Machine learning in finance: the landscape -- Developing a machine learning model in Python -- Artificial neural networks -- Part 2. Supervised learning. Supervised learning : models and concepts -- Supervised learning : regression (including time series models) -- Supervised learning : classification -- Part 3. Unsupervised learning. Unsupervised learning : dimensionality reduction -- Unsupervised learning : clustering -- Part 4. Reinforcement learning and natural language processing. Reinforcement learning -- Natural language processing.▲ | |
| 520 | ▼aMachine learning and data science will significantly transform the finance industry in the next few years. With this practical guide, professionals at hedge funds, investment and retail banks, and fintech firms will learn how to build ML algorithms crucial to this industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).▲ | ||
| 650 | 0 | ▼aFinance▼xData processing.▲ | |
| 650 | 0 | ▼aFinance▼xMathematical models.▲ | |
| 650 | 0 | ▼aMachine learning.▲ | |
| 650 | 0 | ▼aNatural language processing (Computer science)▲ | |
| 650 | 0 | ▼aPython (Computer program language)▲ | |
| 700 | 1 | ▼aPuri, Sahil.▲ | |
| 700 | 1 | ▼aLookabaugh, Brad.▲ |
Machine learning and data science blueprints for finance : from building trading strategies to robo-advisors using Python
자료유형
국외단행본
서명/책임사항
Machine learning and data science blueprints for finance : from building trading strategies to robo-advisors using Python / by Hariom Tatsat, Sahil Puri, Brad Lookabaugh.
발행사항
Sebastopol, CA : O'Reilly Media , 2020.
형태사항
xv, 409 p. : ill. ; 24 cm
일반주기
Includes index.
내용주기
Part 1. The framework. Machine learning in finance: the landscape -- Developing a machine learning model in Python -- Artificial neural networks -- Part 2. Supervised learning. Supervised learning : models and concepts -- Supervised learning : regression (including time series models) -- Supervised learning : classification -- Part 3. Unsupervised learning. Unsupervised learning : dimensionality reduction -- Unsupervised learning : clustering -- Part 4. Reinforcement learning and natural language processing. Reinforcement learning -- Natural language processing.
요약주기
Machine learning and data science will significantly transform the finance industry in the next few years. With this practical guide, professionals at hedge funds, investment and retail banks, and fintech firms will learn how to build ML algorithms crucial to this industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).
주제
ISBN
1492073059 9781492073055
청구기호
006.31 T219m
소장정보
예도서예약
서서가에없는책 신고
보보존서고신청
캠캠퍼스대출
우우선정리신청
배자료배달신청
문문자발송
출청구기호출력
학소장학술지 원문서비스
| 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 서비스 |
|---|
북토크
자유롭게 책을 읽고
느낀점을 적어주세요
글쓰기
느낀점을 적어주세요
청구기호 브라우징
관련 인기대출 도서