مكتبة جامعة عجلون الوطنية

فهرس بحث المكتبة

Python for scientific computation and artificial intelligence / Stephen Lynch.

By: Material type: TextLanguage: English Series: Chapman & Hall/CRC the Python seriesPublisher: Boca Raton : C&H/CRC Press, 2023Edition: First editionDescription: pages cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781032258737
  • 9781032258713
Subject(s): Additional physical formats: Online version:: Python for scientific computation and artificial intelligence.DDC classification:
  • 005.13/3 23/eng/20230125
LOC classification:
  • QA76.73.P98 L96 2023
Contents:
The idle integrated development learning environment -- Anaconda, Spyder and the Libraries Numpy, Matplotlib and Sympy -- Jupyter Notebooks and Google Colab -- Python for AS-level (high school) mathematics -- Python for A-level (high school) mathematics -- Biology -- Chemistry -- Data science -- Economics -- Engineering -- Fractals and multifractals -- Image processing -- Numerical methods for ordinary and partial differential equations -- Physics -- Statistics -- Brain inspired computing -- Neural networks and neurodynamics -- Tensorflow and keras -- Recurrent neural networks -- Convolutional neural networks, tensorboard, and further reading -- Answers and hints to exercises.
Summary: "Python for Scientific Computation 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"-- Provided by publisher.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Cover image Item type Current library Home library Collection Shelving location Call number Materials specified Vol info URL Copy number Status Notes Date due Barcode Item holds Item hold queue priority Course reserves
Books مكتبة جامعة عجلون الوطنية QA76.73.P98.L96 2023 (Browse shelf(Opens below)) Available E3975
Books مكتبة جامعة عجلون الوطنية QA76.73.P98.L96 2023 (Browse shelf(Opens below)) Available E3976

Includes bibliographical references and index.

The idle integrated development learning environment -- Anaconda, Spyder and the Libraries Numpy, Matplotlib and Sympy -- Jupyter Notebooks and Google Colab -- Python for AS-level (high school) mathematics -- Python for A-level (high school) mathematics -- Biology -- Chemistry -- Data science -- Economics -- Engineering -- Fractals and multifractals -- Image processing -- Numerical methods for ordinary and partial differential equations -- Physics -- Statistics -- Brain inspired computing -- Neural networks and neurodynamics -- Tensorflow and keras -- Recurrent neural networks -- Convolutional neural networks, tensorboard, and further reading -- Answers and hints to exercises.

"Python for Scientific Computation 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"-- Provided by publisher.

Share