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Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Name: Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
Price: 27.99 USD
Availability: InStock
Rating: 4.5 (138 reviews)

4.5 of 5 Stars: Programming Languages - Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

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$27.99

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Description

Book Synopsis: Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for 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
Plot and visualize data with Matplotlib
Perform data analysis tasks with Pandas and SciPy
Review statistical modeling and machine learning with statsmodels and scikit-learn
Optimize Python code using Numba and Cython

Who This Book Is For

Developers who want to understand how to use Python and its related ecosystem for numerical computing.

Details

Looking to leverage the power of Python for numerical computing and data science? Look no further than Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib. This fully revised edition provides all the tools and resources you need to harness the numerical and mathematical modules in Python and its standard library, along with popular open source packages like NumPy, SciPy, FiPy, and matplotlib.

Whether you're working with big data, cloud computing, financial engineering, or business management, this book is your go-to guide. Packed with brand-new case studies, you'll find real-world examples of data science and statistics applications in Python, demonstrating its versatility and efficiency. With its simple and high-level syntax, Python allows for rapid development and exploratory computing, making it perfect for any computing task.

Not only will you learn how to work with vectors and matrices using NumPy, but you'll also gain expertise in plotting and visualizing data with Matplotlib. Perform data analysis tasks with Pandas and SciPy, and explore statistical modeling and machine learning with statsmodels and scikit-learn. Plus, you'll discover how to optimize your Python code using Numba and Cython for maximum efficiency.

Whether you're a developer or data enthusiast, Numerical Python is your ultimate resource for understanding and utilizing Python and its related ecosystem for numerical computing. Don't miss out on this opportunity to enhance your computational skills and take your data science projects to the next level.

Ready to unlock the power of Python for numerical computing? Get your copy of Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib today!

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