Applying Math with Python Over 70 Practical Recipes for Solving Real-World Computational Math Problems.

The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by...

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Bibliographic Details
Main Author: Morley, Sam.
Format: Electronic
Language: English
Published: Birmingham : Packt Publishing, Limited, 2022.
Edition: 2nd ed.
Subjects:
ISBN: 9781804616802
180461680X
9781804618370
Physical Description: 1 online resource (376 p.)

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Summary: The updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX. You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you've developed a solid base in these topics, you'll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
Item Description: Description based upon print version of record.
Chapter 4: Working with Randomness and Probability
Bibliography: Includes bibliographical references and index.
ISBN: 9781804616802
180461680X
9781804618370
Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty