Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
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 numer...
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| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berkeley, CA
Apress
[2024]
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| Edition: | Third Edition |
| Subjects: | |
| Summary: | 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 Learn- Work with vectors and matrices using NumPy- Review Symbolic computing with SymPy- Plot and visualize data with Matplotlib- Perform data analysis tasks with Pandas and SciPy- Understand statistical modeling and machine learning with statsmodels and scikit-learn- Optimize 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 |
| Physical Description: | xx, 492 Seiten Illustrationen, Diagramme 254 mm |
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| 520 | |a 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 Learn- Work with vectors and matrices using NumPy- Review Symbolic computing with SymPy- Plot and visualize data with Matplotlib- Perform data analysis tasks with Pandas and SciPy- Understand statistical modeling and machine learning with statsmodels and scikit-learn- Optimize 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 | ||
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| spelling | Johansson, Robert 1977- Verfasser (DE-588)136985262 aut Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib Robert Johansson Third Edition Berkeley, CA Apress [2024] xx, 492 Seiten Illustrationen, Diagramme 254 mm txt rdacontent n rdamedia nc rdacarrier 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 Learn- Work with vectors and matrices using NumPy- Review Symbolic computing with SymPy- Plot and visualize data with Matplotlib- Perform data analysis tasks with Pandas and SciPy- Understand statistical modeling and machine learning with statsmodels and scikit-learn- Optimize 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 Computer software Big data Artificial intelligence Python (Computer program language) Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Wissenschaftliches Rechnen (DE-588)4338507-2 gnd rswk-swf Hardcover, Softcover / Informatik, EDV/Programmiersprachen Wissenschaftliches Rechnen (DE-588)4338507-2 s Python Programmiersprache (DE-588)4434275-5 s DE-604 Erscheint auch als Online-Ausgabe 979-8-8688-0413-7 |
| spellingShingle | Johansson, Robert 1977- Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib Computer software Big data Artificial intelligence Python (Computer program language) Python Programmiersprache (DE-588)4434275-5 gnd Wissenschaftliches Rechnen (DE-588)4338507-2 gnd |
| subject_GND | (DE-588)4434275-5 (DE-588)4338507-2 |
| title | Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib |
| title_auth | Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib |
| title_exact_search | Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib |
| title_full | Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib Robert Johansson |
| title_fullStr | Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib Robert Johansson |
| title_full_unstemmed | Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib Robert Johansson |
| title_short | Numerical Python |
| title_sort | numerical python scientific computing and data science applications with numpy scipy and matplotlib |
| title_sub | Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib |
| topic | Computer software Big data Artificial intelligence Python (Computer program language) Python Programmiersprache (DE-588)4434275-5 gnd Wissenschaftliches Rechnen (DE-588)4338507-2 gnd |
| topic_facet | Computer software Big data Artificial intelligence Python (Computer program language) Python Programmiersprache Wissenschaftliches Rechnen |
| work_keys_str_mv | AT johanssonrobert numericalpythonscientificcomputinganddatascienceapplicationswithnumpyscipyandmatplotlib |