
Mastering Numerical Computing with NumPy
Master scientific computing and perform complex operations with ease
De Gruyter (Verlag)
1. Auflage
Erschienen am 23. September 2024
248 Seiten
978-1-78899-684-6 (ISBN)
Systemvoraussetzungen
für ePUB mit Adobe-DRM
E-Book Einzellizenz
Bei dem Kauf dieses E-Books erwerben Sie eine Einzel-Lizenz für eine natürliche Person, die nicht übertragbar ist. [L]
Als Download verfügbar
Beschreibung
No detailed description available for "Mastering Numerical Computing with NumPy".
Weitere Details
Sprache
Englisch
Verlagsort
Basel/Berlin/Boston
Großbritannien
Zielgruppe
Für Beruf und Forschung
Editions-Typ
Digitale Ausgabe
Dateigröße
14,54 MB
ISBN-13
978-1-78899-684-6 (9781788996846)
Schweitzer Klassifikation
Weitere Ausgaben
Personen
Mert Cakmak Umit :
Umit Mert Cakmak is a data scientist at IBM, where he excels at helping clients solve complex data science problems, from inception to delivery of deployable assets. His research spans multiple disciplines beyond his industry and he likes sharing his insights at conferences, universities, and meet-ups.Antao Tiago :
Tiago Antao is a bioinformatician currently working in the field of genomics. A former computer scientist, Tiago moved into computational biology with an MSc in Bioinformatics from the Faculty of Sciences at the University of Porto (Portugal) and a PhD on the spread of drug-resistant malaria from the Liverpool School of Tropical Medicine (UK). Postdoctoral, Tiago has worked with human datasets at the University of Cambridge (UK) and with mosquito whole genome sequencing data at the University of Oxford (UK), before helping to set up the bioinformatics infrastructure at the University of Montana. He currently works as a data engineer in the biotechnology field in Boston, MA. He is one of the co-authors of Biopython, a major bioinformatics package written in Python.Cuhadaroglu Mert :
Mert Cuhadaroglu is a BI Developer in EPAM, developing E2E analytics solutions for complex business problems in various industries, mostly investment banking, FMCG, media, communication, and pharma. He consistently uses advanced statistical models and ML algorithms to provide actionable insights. Throughout his career, he has worked in several other industries, such as banking and asset management. He continues his academic research in AI for trading algorithms.
Umit Mert Cakmak is a data scientist at IBM, where he excels at helping clients solve complex data science problems, from inception to delivery of deployable assets. His research spans multiple disciplines beyond his industry and he likes sharing his insights at conferences, universities, and meet-ups.Antao Tiago :
Tiago Antao is a bioinformatician currently working in the field of genomics. A former computer scientist, Tiago moved into computational biology with an MSc in Bioinformatics from the Faculty of Sciences at the University of Porto (Portugal) and a PhD on the spread of drug-resistant malaria from the Liverpool School of Tropical Medicine (UK). Postdoctoral, Tiago has worked with human datasets at the University of Cambridge (UK) and with mosquito whole genome sequencing data at the University of Oxford (UK), before helping to set up the bioinformatics infrastructure at the University of Montana. He currently works as a data engineer in the biotechnology field in Boston, MA. He is one of the co-authors of Biopython, a major bioinformatics package written in Python.Cuhadaroglu Mert :
Mert Cuhadaroglu is a BI Developer in EPAM, developing E2E analytics solutions for complex business problems in various industries, mostly investment banking, FMCG, media, communication, and pharma. He consistently uses advanced statistical models and ML algorithms to provide actionable insights. Throughout his career, he has worked in several other industries, such as banking and asset management. He continues his academic research in AI for trading algorithms.
Inhalt
Table of Contents - Working with NumPy Arrays
- Linear Algebra with NumPy
- Explanatory Data Analysis of US Housing Data withNumPy Statistics
- Predicting Housing Prices Using Linear Regression
- Clustering Clients of Wholesale Distributor Using NumPy
- Python ML Squad: NumPy, SciPy, Pandas, Scikit-Learn
- Advanced Numpy
- Overview of High-Performance Numerical Computing Libraries
- Performance Benchmarks
- Linear Algebra with NumPy
- Explanatory Data Analysis of US Housing Data withNumPy Statistics
- Predicting Housing Prices Using Linear Regression
- Clustering Clients of Wholesale Distributor Using NumPy
- Python ML Squad: NumPy, SciPy, Pandas, Scikit-Learn
- Advanced Numpy
- Overview of High-Performance Numerical Computing Libraries
- Performance Benchmarks
Systemvoraussetzungen
Dateiformat: ePUB
Kopierschutz: Adobe-DRM (Digital Rights Management)
Systemvoraussetzungen:
- Computer (Windows; MacOS X; Linux): Installieren Sie bereits vor dem Download die kostenlose Software Adobe Digital Editions (siehe E-Book Hilfe).
- Tablet/Smartphone (Android; iOS): Installieren Sie bereits vor dem Download die kostenlose App Adobe Digital Editions oder die App PocketBook (siehe E-Book Hilfe).
- E-Book-Reader: Bookeen, Kobo, Pocketbook, Sony, Tolino u.v.a.m. (nicht Kindle)
Das Dateiformat ePUB ist sehr gut für Romane und Sachbücher geeignet – also für „fließenden” Text ohne komplexes Layout. Bei E-Readern oder Smartphones passt sich der Zeilen- und Seitenumbruch automatisch den kleinen Displays an.
Mit Adobe-DRM wird hier ein „harter” Kopierschutz verwendet. Wenn die notwendigen Voraussetzungen nicht vorliegen, können Sie das E-Book leider nicht öffnen. Daher müssen Sie bereits vor dem Download Ihre Lese-Hardware vorbereiten.
Bitte beachten Sie: Wir empfehlen Ihnen unbedingt nach Installation der Lese-Software diese mit Ihrer persönlichen Adobe-ID zu autorisieren!
Weitere Informationen finden Sie in unserer E-Book Hilfe.