NumPy :: beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library /
This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and poi...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2015.
|
| Ausgabe: | 3rd edition. |
| Schriftenreihe: | Learn by doing : less theory, more results.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources. |
| Beschreibung: | Includes index. |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| ISBN: | 9781785288838 1785288830 |
Internformat
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| contents | Chapter 1: NumPy Quick Start -- Chapter 2: Beginning with NumPy Fundamentals -- Chapter 3: Getting Familiar with Commonly Used Functions -- Chapter 4: Convenience Functions for Your Convenience -- Chapter 5: Working with Matrices and ufuncs -- Chapter 6: Moving Further with NumPy Modules -- Chapter 7: Peeking Into Special Routines -- Chapter 8: Assure Quality with Testing -- Chapter 9: Plotting with matplotlib -- Chapter 10: When NumPy is Not enough -- SciPy and Beyond. |
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| discipline | Informatik |
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| spelling | Idris, Ivan, author. NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / Ivan Idris. Build efficient, high-speed programs using the high-performance NumPy mathematical library 3rd edition. Birmingham, UK : Packt Publishing, 2015. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier text file Learn by doing : less theory, more results Online resource; title from cover (Safari, viewed July 6, 2015). Includes index. Chapter 1: NumPy Quick Start -- Chapter 2: Beginning with NumPy Fundamentals -- Chapter 3: Getting Familiar with Commonly Used Functions -- Chapter 4: Convenience Functions for Your Convenience -- Chapter 5: Working with Matrices and ufuncs -- Chapter 6: Moving Further with NumPy Modules -- Chapter 7: Peeking Into Special Routines -- Chapter 8: Assure Quality with Testing -- Chapter 9: Plotting with matplotlib -- Chapter 10: When NumPy is Not enough -- SciPy and Beyond. This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources. English. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Numerical analysis Data processing. Python (Langage de programmation) Analyse numérique Informatique. COMPUTERS General. bisacsh Numerical analysis Data processing fast Python (Computer program language) fast has work: NumPy (Text) https://id.oclc.org/worldcat/entity/E39PCXwMrPqTjXfqQPXvpvYRH3 https://id.oclc.org/worldcat/ontology/hasWork Print version: Idris, Ivan. NumPy beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library. Third edition. Birmingham, England : Packt Publishing, ©2015 xvi, 317 pages 9781785281969 Learn by doing : less theory, more results. FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1018109 Volltext CBO01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1018109 Volltext |
| spellingShingle | Idris, Ivan NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / Learn by doing : less theory, more results. Chapter 1: NumPy Quick Start -- Chapter 2: Beginning with NumPy Fundamentals -- Chapter 3: Getting Familiar with Commonly Used Functions -- Chapter 4: Convenience Functions for Your Convenience -- Chapter 5: Working with Matrices and ufuncs -- Chapter 6: Moving Further with NumPy Modules -- Chapter 7: Peeking Into Special Routines -- Chapter 8: Assure Quality with Testing -- Chapter 9: Plotting with matplotlib -- Chapter 10: When NumPy is Not enough -- SciPy and Beyond. Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Numerical analysis Data processing. Python (Langage de programmation) Analyse numérique Informatique. COMPUTERS General. bisacsh Numerical analysis Data processing fast Python (Computer program language) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh96008834 |
| title | NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / |
| title_alt | Build efficient, high-speed programs using the high-performance NumPy mathematical library |
| title_auth | NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / |
| title_exact_search | NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / |
| title_full | NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / Ivan Idris. |
| title_fullStr | NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / Ivan Idris. |
| title_full_unstemmed | NumPy : beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / Ivan Idris. |
| title_short | NumPy : |
| title_sort | numpy beginner s guide build efficient high speed programs using the high performance numpy mathematical library |
| title_sub | beginner's guide : build efficient, high-speed programs using the high-performance NumPy mathematical library / |
| topic | Python (Computer program language) http://id.loc.gov/authorities/subjects/sh96008834 Numerical analysis Data processing. Python (Langage de programmation) Analyse numérique Informatique. COMPUTERS General. bisacsh Numerical analysis Data processing fast Python (Computer program language) fast |
| topic_facet | Python (Computer program language) Numerical analysis Data processing. Python (Langage de programmation) Analyse numérique Informatique. COMPUTERS General. Numerical analysis Data processing |
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