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Ajouter au panierEtat : Acceptable. Readable, but has significant damage / tears. Has a remainder mark. paperback Used - Acceptable 2018.
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Ajouter au panierPaperback. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Apress
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Ajouter au panierpaperback. Etat : VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.
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Ajouter au panierPaperback. Etat : Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Edité par Apress, 2024
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Ajouter au panierpaperback. Etat : Fine.
Edité par Apress, 2024
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Ajouter au panierpaperback. Etat : Very Good.
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Ajouter au panierPaperback. Etat : new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Vendeur : Studibuch, Stuttgart, Allemagne
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Ajouter au panierpaperback. Etat : Sehr gut. 723 Seiten; 9781484242452.2 Gewicht in Gramm: 2.
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Ajouter au panierTaschenbuch. Etat : Neu. Numerical Python | Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib | Robert Johansson | Taschenbuch | xx | Englisch | 2024 | Apress | EAN 9798868804120 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Vendeur : Blue Vase Books, Interlochen, MI, Etats-Unis
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Ajouter au panierEtat : very_good. Book has little sign of wear or use.
Vendeur : medimops, Berlin, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Learn how to leverage the scientific computing and data analysis capabilities of Python, its standard library, and popular open-source numerical Python packages like NumPy, SymPy, SciPy, matplotlib, and more. This book demonstrates how to work with mathematical modeling and solve problems with numerical, symbolic, and visualization techniques. It explores applications in science, engineering, data analytics, and more.Numerical Python, Third Edition, presents many case study examples of applications in fundamental scientific computing disciplines, as well as in data science and statistics. This fully revised edition, updated for each library's latest version, demonstrates Python's power for rapid development and exploratory computing due to its simple and high-level syntax and many powerful libraries and tools for computation and data analysis.After reading this book, readers will be familiar with many computing techniques, including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling, and machine learning.What You'll LearnWork with vectors and matrices using NumPyReview Symbolic computing with SymPyPlot and visualize data with MatplotlibPerform data analysis tasks with Pandas and SciPyUnderstand statistical modeling and machine learning with statsmodels and scikit-learnOptimize Python code using Numba and CythonWho This Book Is ForDevelopers who want to understand how to use Python and its ecosystem of libraries for scientific computing and data analysis.