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Nº de artículo:
18317338
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
88% of respondents would recommend this to a friend
Nº de artículo:
18317338
UYU 4229
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Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python
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What Stands Out
Comprehensive Learning
This edition provides an extensive overview of essential libraries like NumPy, SciPy, and Matplotlib, ideal for anyone looking to deepen their understanding of scientific computing and data science.
Practical Applications
Focuses on real-world applications and scenarios, enabling users to apply learned techniques directly to data science problems, enhancing practical skills and problem-solving abilities.
Updated Content
Includes the latest advancements and best practices in data science and scientific computing, ensuring readers are equipped with current knowledge to stay competitive in the field.
Detalles de producto
- Fully revised edition covering numerical and mathematical modules in Python and popular open source packages like NumPy, SciPy, FiPy, and matplotlib
- Demonstrates numerically computing solutions and modeling applications in big data, cloud computing, financial engineering, and business management
- Presents new case study examples of applications in data science, statistics, and extensions to previous examples
- Covers array-based and symbolic computing, visualization, numerical file I/O, equation solving, optimization, interpolation, integration, and domain-specific computational problems
- Learn to work with vectors, matrices, plot and visualize data, perform data analysis tasks, review statistical modeling, and optimize Python code
- Ideal for developers seeking to understand how to use Python and its ecosystem for numerical computing
| Package Weight | 3.0500 Pound |
Who Should Buy?
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Data Scientists
Ideal for data scientists needing a comprehensive resource on Python libraries for data manipulation and analysis.
-
Researchers
Helpful for researchers in academia looking to incorporate Python for scientific computing and statistical modeling.
-
Students
Great for students learning numerical methods, data analysis, and programming with practical examples and applications.
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Beginners
Not suitable for complete programming beginners unfamiliar with Python or programming concepts, as it requires prior knowledge.
DESCRIPCIÓN DEL PRODUCTO
Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
About This Item
Unlock the power of scientific computing and data science with Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy, and Matplotlib. This 2nd edition is packed with everything you need to master Python for numerical analysis, data analysis, and more. If you're a data enthusiast, scientist, or researcher, this book is a must-have. Dive deep into the world of Python and learn how to leverage its libraries and tools for scientific computing and data science applications.
With Numerical Python, you'll discover the power of Numpy, SciPy, and Matplotlib to analyze, visualize, and model data. The book covers various topics such as numerical methods in Python, data analysis, data exploration, and statistical analysis. You'll also learn about Python's applications in areas like mathematical modeling, simulation, and data mining. But it doesn't stop there.
Numerical Python also delves into advanced concepts like machine learning, big data analytics, and predictive analytics in Python. You'll discover how to use Python's data science frameworks and libraries to tackle complex problems and make accurate predictions. With clear explanations, practical examples, and hands-on exercises, Numerical Python is designed to help you grasp the concepts and apply them in real-world scenarios. Whether you're a beginner or an experienced programmer, this book provides a comprehensive guide to Python for scientific computing and data science. Don't miss out on the opportunity to enhance your skills and take your data analysis to the next level.
Get your copy of Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy, and Matplotlib now.
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Intelligence & Semantics Editorial Review
The Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib 2nd ed. Edition offers a comprehensive guide to scientific computing and data science applications with Python. The book covers key libraries like Numpy, Scipy, and Matplotlib, and is organized in a logical, easy-to-follow manner. It is a great tool for those looking to build python skills in data science and scientific computing.
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ventajas
- Comprehensive guide to scientific computing and data science applications
- Covers key libraries like Numpy, Scipy, and Matplotlib
- Organized in a logical, easy-to-follow manner
Contras
- Some customers received a product with low-quality paper and poor print material
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características y beneficios
- Leverage numerical and mathematical modules in Python
- Use popular open-source numerical Python packages
- Compute solutions and mathematically model applications
- Learn array-based and symbolic computing
- Perform data analysis, statistical modeling, and machine learning
- Optimize Python code for numerical computing
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