Scientific Computing with Python 3

Discover how to leverage Python 3 for scientific and numerical computing with 'Scientific Computing with Python 3'. This comprehensive guide walks you through the essential tools and libraries, such as NumPy and SciPy, enabling you to implement practical mathematical solutions using Python. Gain valuable skills to efficiently solve computational problems and create insightful visualizations.

What this Book will help me do

• Gain a solid understanding of Python's syntax and data types for scientific computing applications.
• Learn to work with core libraries such as NumPy and SciPy for efficient numerical computation.
• Efficiently utilize Python for linear algebra operations and advanced array manipulations.
• Create clear and engaging data visualizations using Matplotlib in Python.
• Develop robust and testable Python code, mastering techniques like exception handling and testing strategies.

Author(s)

Claus Fuhrer, None Führer, None Solem, and None Verdier bring a wealth of expertise in computational mathematics and programming to this book. With a strong background in teaching and professional practice, they've carefully crafted this resource to be accessible and valuable. Their real-world insights and illustrative examples make this book a practical guide for learners and practitioners.

Who is it for?

This book is ideal for developers, data analysts, and students interested in scientific and numerical computing. If you have some familiarity with mathematical concepts and want to expand your Python skills toward applied computation, this book is for you. Beginners in Python programming will find it accessible, and intermediate users will appreciate the depth of the topics covered. Whether you're in academia or industry, 'Scientific Computing with Python 3' provides the tools to advance your knowledge and capabilities.