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Machine Learning and Big Data with KDB+/Q : Q, High Frequency Financial Data and Algorithmic Trading.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Bilokon, Paul A.
Otros Autores: Novotny, Jan
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2019.
Temas:
Acceso en línea:Texto completo

MARC

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040 |a EBLCP  |b eng  |e pn  |c EBLCP  |d OCLCQ  |d REDDC  |d OCLCO  |d OCLCL 
020 |a 9781119404743 
020 |a 1119404746 
035 |a (OCoLC)1128465997 
050 4 |a HG4515.5  |b .N686 2020 
082 0 4 |a 005.74  |q OCoLC  |2 23/eng/20230216 
049 |a UAMI 
100 1 |a Bilokon, Paul A. 
245 1 0 |a Machine Learning and Big Data with KDB+/Q :  |b Q, High Frequency Financial Data and Algorithmic Trading. 
260 |a Newark :  |b John Wiley & Sons, Incorporated,  |c 2019. 
300 |a 1 online resource (640 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Print version record. 
505 0 |a Cover; Title Page; Copyright; Contents; Preface; History of Kdb+ and q; Motivation for this Book; Code Structure; Structure of the Book; Prerequisites; About the Authors; Part One Language Fundamentals; Chapter 1 Fundamentals of the q Programming Language; 1.1 The (Not So Very) First Steps in q; 1.2 Atoms and Lists; 1.2.1 Casting Types; 1.3 Basic Language Constructs; 1.3.1 Assigning, Equality and Matching; 1.3.2 Arithmetic Operations and Right-to-Left Evaluation: Introduction to q Philosophy; 1.4 Basic Operators; 1.5 Difference between Strings and Symbols; 1.5.1 Enumeration 
505 8 |a 1.6 Matrices and Basic Linear Algebra in q1.7 Launching the Session: Additional Options; 1.8 Summary and How-To's; Chapter 2 Dictionaries and Tables: The q Fundamentals; 2.1 Dictionary; 2.2 Table; 2.3 The Truth about Tables; 2.4 Keyed Tables Are Dictionaries; 2.5 From a Vector Language to an Algebraic Language; Chapter 3 Functions; 3.1 Namespace; 3.1.0.1 .quantQ. Namespace; 3.2 The Six Adverbs; 3.2.1 Each; 3.2.1.1 Each; 3.2.1.2 Each-left \:; 3.2.1.3 Each-right /:; 3.2.1.4 Cross Product /: \:; 3.2.1.5 Each-both '; 3.2.2 Each-prior ':; 3.2.3 Compose ('); 3.2.4 Over and Fold /; 3.2.5 Scan 
505 8 |a 3.2.5.1 EMA: The Exponential Moving Average3.2.6 Converge; 3.2.6.1 Converge-repeat; 3.2.6.2 Converge-iterate; 3.3 Apply; 3.3.1 @ (apply); 3.3.2 . (apply); 3.4 Protected Evaluations; 3.5 Vector Operations; 3.5.1 Aggregators; 3.5.1.1 Simple Aggregators; 3.5.1.2 Weighted Aggregators; 3.5.2 Uniform Functions; 3.5.2.1 Running Functions; 3.5.2.2 Window Functions; 3.6 Convention for User-Defined Functions; Chapter 4 Editors and Other Tools; 4.1 Console; 4.2 Jupyter Notebook; 4.3 GUIs; 4.3.1 qStudio; 4.3.2 Q Insight Pad; 4.4 IDEs: IntelliJ IDEA; 4.5 Conclusion; Chapter 5 Debugging q Code 
505 8 |a 5.1 Introduction to Making It Wrong: Errors5.1.1 Syntax Errors; 5.1.2 Runtime Errors; 5.1.2.1 The Type Error; 5.1.2.2 Other Errors; 5.2 Debugging the Code; 5.3 Debugging Server-Side; Part Two Data Operations; Chapter 6 Splayed and Partitioned Tables; 6.1 Introduction; 6.2 Saving a Table as a Single Binary File; 6.3 Splayed Tables; 6.4 Partitioned Tables; 6.5 Conclusion; Chapter 7 Joins; 7.1 Comma Operator; 7.2 Join Functions; 7.2.1 ij; 7.2.2 ej; 7.2.3 lj; 7.2.4 pj; 7.2.5 upsert; 7.2.6 uj; 7.2.7 aj; 7.2.8 aj0; 7.2.8.1 The Next Valid Join; 7.2.9 asof; 7.2.10 wj 
505 8 |a 7.3 Advanced Example: Running TWAPChapter 8 Parallelisation; 8.1 Parallel Vector Operations; 8.2 Parallelisation over Processes; 8.3 Map-Reduce; 8.4 Advanced Topic: Parallel File/Directory Access; Chapter 9 Data Cleaning and Filtering; 9.1 Predicate Filtering; 9.1.1 The Where Clause; 9.1.2 Aggregation Filtering; 9.2 Data Cleaning, Normalising and APIs; Chapter 10 Parse Trees; 10.1 Definition; 10.1.1 Evaluation; 10.1.2 Parse Tree Creation; 10.1.3 Read-Only Evaluation; 10.2 Functional Queries; 10.2.1 Functional Select; 10.2.2 Functional Exec; 10.2.3 Functional Update; 10.2.4 Functional Delete 
500 |a Chapter 11 A Few Use Cases 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Investments  |x Data processing. 
650 6 |a Investissements  |x Informatique. 
700 1 |a Novotny, Jan. 
758 |i has work:  |a Machine learning and big data with kdb+/q (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCG3G83pmR6kwCCb6Y9T3pP  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Bilokon, Paul A.  |t Machine Learning and Big Data with KDB+/Q : Q, High Frequency Financial Data and Algorithmic Trading.  |d Newark : John Wiley & Sons, Incorporated, ©2019  |z 9781119404750 
856 4 0 |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5977946  |z Texto completo 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL5977946 
994 |a 92  |b IZTAP