Python for Scientific Computing and Artificial Intelligence by Stephen Lynch

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Book Title
Python for Scientific Computing and Artificial Intelligence
Publication Date
2023-06-15
Pages
314
ISBN
9781032258713
類別

關於產品

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1032258713
ISBN-13
9781032258713
eBay Product ID (ePID)
20058628380

Product Key Features

Number of Pages
344 Pages
Publication Name
Python for Scientific Computing and Artificial Intelligence
Language
English
Publication Year
2023
Subject
Computer Science, General, Applied, Programming Languages / Python
Type
Textbook
Subject Area
Mathematics, Computers
Author
Stephen Lynch
Series
Chapman and Hall/Crc the Python Ser.
Format
Trade Paperback

Dimensions

Item Length
10 in
Item Width
7 in

Additional Product Features

Intended Audience
Trade
LCCN
2022-057798
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
005.133
Table Of Content
Section I. An Introduction to Python. 1. The IDLE Integrated Development Learning Environment. 2. Anaconda, Spyder and the Libraries NumPy, Matplotlib and SymPy. 3. Jupyter Notebooks and Google Colab. 4. Python for AS-Level (High School) Mathematics. 5. Python for A-Level (High School) Mathematics. Section II. Python for Scientific Computing. 6. Biology. 7. Chemistry. 8. Data Science. 9. Economics. 10. Engineering. 11. Fractals and Multifractals. 12. Image Processing. 13. Numerical Methods for Ordinary and Partial Differential Equations. 14. Physics. 15. Statistics. Section III. Artificial Intelligence. 16. Brain Inspired Computing. 17. Neural Networks and Neurodynamics. 18. TensorFlow and Keras. 19. Recurrent Neural Networks. 20. Convolutional Neural Networks, TensorBoard, and Further Reading. 21. Answers and Hints to Exercises.
Synopsis
Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features : No prior experience of programming is required Online GitHub repository available with codes for readers to practice Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing Full solutions to exercises are available as Jupyter notebooks on the Web Support Material GitHub Repository of Python Files and Notebooks: https: //github.com/proflynch/CRC-Press/ Solutions to All Exercises: Section 1: An Introduction to Python: https: //drstephenlynch.github.io/webpages/Solutions_Section_1.html Section 2: Python for Scientific Computing: https: //drstephenlynch.github.io/webpages/Solutions_Section_2.html Section 3: Artificial Intelligence: https: //drstephenlynch.github.io/webpages/Solutions_Section_3.ht, Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web., This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling.
LC Classification Number
QA76.73.P98L96 2023

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