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The Python Audio Cookbook Recipes for Audio Scripting with Python

The Python Audio Cookbook Recipes for Audio Scripting with Python

The Python Audio Cookbook offers an introduction to Python for sound and multimedia applications with chapters that cover writing your first Python programs controlling Pyo with physical computing and writing your own GUI among many other topics. Guiding the reader through a variety of audio synthesis techniques the book empowers readers to combine their projects with popular platforms from the Arduino to Twitter and state-of-the-art practices such as AI. The Python Audio Cookbook balances accessible explanations for theoretical concepts including Python syntax audio processing and machine learning with practical applications. This book is an essential introductory guide to Python for sound and multimedia practitioners as well as programmers interested in audio applications. | The Python Audio Cookbook Recipes for Audio Scripting with Python

GBP 31.99
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Python for Beginners

Python for Beginners

Python is an amazing programming language. It can be applied to almost any programming task. It allows for rapid development and debugging. Getting started with Python is like learning any new skill: it’s important to find a resource you connect with to guide your learning. Luckily there’s no shortage of excellent books that can help you learn both the basic concepts of programming and the specifics of programming in Python. With the abundance of resources it can be difficult to identify which book would be best for your situation. Python for Beginners is a concise single point of reference for all material on python. Provides concise need-to-know information on Python types and statements special method names built-in functions and exceptions commonly used standard library modules and other prominent Python tools Offers practical advice for each major area of development with both Python 3. x and Python 2. x Based on the latest research in cognitive science and learning theory Helps the reader learn how to write effective idiomatic Python code by leveraging its best—and possibly most neglected—features This book focuses on enthusiastic research aspirants who work on scripting languages for automating the modules and tools development of web applications handling big data complex calculations workflow creation rapid prototyping and other software development purposes. It also targets graduates postgraduates in computer science information technology academicians practitioners and research scholars.

GBP 120.00
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Python Packages

Python Packages

Python Packages introduces Python packaging at an introductory and practical level that’s suitable for those with no previous packaging experience. Despite this the text builds up to advanced topics such as automated testing creating documentation versioning and updating a package and implementing continuous integration and deployment. Covering the entire Python packaging life cycle this essential guide takes readers from package creation all the way to effective maintenance and updating. Python Packages focuses on the use of current and best-practice packaging tools and services like poetry cookiecutter pytest sphinx GitHub and GitHub Actions. Features: The book’s source code is available online as a GitHub repository where it is collaborated on automatically tested and built in real time as changes are made; demonstrating the use of good reproducible and clear project workflows. Covers not just the process of creating a package but also how to document it test it publish it to the Python Package Index (PyPI) and how to properly version and update it. All concepts in the book are demonstrated using examples. Readers can follow along creating their own Python packages using the reproducible code provided in the text. Focuses on a modern approach to Python packaging with emphasis on automating and streamlining the packaging process using new and emerging tools such as poetry and GitHub Actions.

GBP 35.99
1

Learning Professional Python Two Volume Set

Learning Professional Python Two Volume Set

Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy understandable manner while strengthening coding skills. Learning Professional Python Objectives: Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes objects inheritance dynamic dispatch interfaces and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications | Learning Professional Python Two Volume Set

GBP 89.99
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Introduction to Python for Humanists

Introduction to Python for Humanists

This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates graduates and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python allowing them to engage with more advanced textbooks. This book fills a real need as it is first Python introduction to be aimed squarely at humanities students as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it in addition to allowing those who are interested in being self-taught can use it for that purpose. Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysis App development | Introduction to Python for Humanists

GBP 44.99
1

Learning Professional Python Volume 2: Advanced

Learning Professional Python Volume 2: Advanced

Volume 2 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy understandable manner while strengthening coding skills. Learning Professional Python: Volume 2 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes objects inheritance dynamic dispatch interfaces and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications | Learning Professional Python Volume 2: Advanced

GBP 52.99
1

Python for Bioinformatics

Python for Bioinformatics

In today's data driven biology programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience Python for Bioinformatics Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts the book focuses on the easy-to-use yet powerful Python computer language. This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases the Anaconda Python distribution graphical libraries like Bokeh and the use of Github for collaborative development.

GBP 74.99
1

Introduction to Computational Models with Python

Introduction to Computational Models with Python

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing such as the Numpy and Scipy modules. The Python source code and data files are available on the author’s website. The book’s five sections present: An overview of problem solving and simple Python programs introducing the basic models and techniques for designing and implementing problem solutions independent of software and hardware toolsProgramming principles with the Python programming language covering basic programming concepts data definitions programming structures with flowcharts and pseudo-code solving problems and algorithmsPython lists arrays basic data structures object orientation linked lists recursion and running programs under LinuxImplementation of computational models with Python using Numpy with examples and case studies The modeling of linear optimization problems from problem formulation to implementation of computational modelsThis book introduces the principles of computational modeling as well as the approaches of multi- and interdisciplinary computing to beginners in the field. It provides the foundation for more advanced studies in scientific computing including parallel computing using MPI grid computing and other methods and techniques used in high-performance computing.

GBP 44.99
1

Modeling and Simulation in Python

Modeling and Simulation in Python

The use of Python as a powerful computational tool is expanding with great strides. Python is a language which is easy to use and the libraries of tools provides it with efficient versatility. As the tools continue to expand users can create insightful models and simulations. While the tools offer an easy method to create a pipeline such constructions are not guaranteed to provide correct results. A lot of things can go wrong when building a simulation - deviously so. Users need to understand more than just how to build a process pipeline. Modeling and Simulation in Python introduces fundamental computational modeling techniques that are used in a variety of science and engineering disciplines. It emphasizes algorithmic thinking skills using different computational environments and includes a number of interesting examples including Shakespeare movie databases virus spread and Chess. Key Features: Several theories and applications are provided each with working Python scripts. All Python functions written for this book are archived on GitHub. Readers do not have to be Python experts but a working knowledge of the language is required. Students who want to know more about the foundations of modeling and simulation will find this an educational and foundational resource.

GBP 82.99
1

Linear Models with Python

Linear Models with Python

Praise for Linear Models with R: This book is a must-have tool for anyone interested in understanding and applying linear models. The logical ordering of the chapters is well thought out and portrays Faraway’s wealth of experience in teaching and using linear models. … It lays down the material in a logical and intricate manner and makes linear modeling appealing to researchers from virtually all fields of study. Biometrical Journal Throughout it gives plenty of insight … with comments that even the seasoned practitioner will appreciate. Interspersed with R code and the output that it produces one can find many little gems of what I think is sound statistical advice well epitomized with the examples chosen…I read it with delight and think that the same will be true with anyone who is engaged in the use or teaching of linear models. Journal of the Royal Statistical Society Like its widely praised best-selling companion version Linear Models with R this book replaces R with Python to seamlessly give a coherent exposition of the practice of linear modeling. Linear Models with Python offers up-to-date insight on essential data analysis topics from estimation inference and prediction to missing data factorial models and block designs. Numerous examples illustrate how to apply the different methods using Python. Features: Python is a powerful open source programming language increasingly being used in data science machine learning and computer science. Python and R are similar but R was designed for statistics while Python is multi-talented. This version replaces R with Python to make it accessible to a greater number of users outside of statistics including those from Machine Learning. A reader coming to this book from an ML background will learn new statistical perspectives on learning from data. Topics include Model Selection Shrinkage Experiments with Blocks and Missing Data. Includes an Appendix on Python for beginners. Linear Models with Python explains how to use linear models in physical science engineering social science and business applications. It is ideal as a textbook for linear models or linear regression courses.

GBP 82.99
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Python for Scientific Computing and Artificial Intelligence

Python for Scientific Computing and Artificial Intelligence

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. html

GBP 52.99
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Understanding Optics with Python

Understanding Optics with Python

Optics is an enabling science that forms a basis for our technological civilization. Courses in optics are a required part of the engineering or physics undergraduate curriculum in many universities worldwide. The aim of Understanding Optics with Python is twofold: first to describe certain basic ideas of classical physical and geometric optics; second to introduce the reader to computer simulations of physical phenomena. The text is aimed more broadly for those who wish to use numerical/computational modeling as an educational tool that promotes interactive teaching (and learning). In addition it offers an alternative to developing countries where the necessary equipment to carry out the appropriate experiments is not available as a result of financial constraints. This approach contributes to a better diffusion of knowledge about optics. The examples given in this book are comparable to those found in standard textbooks on optics and are suitable for self-study. This text enables the user to study and understand optics using hands-on simulations with Python. Python is our programming language of choice because of its open-source availability extensive functionality and an enormous online support. Essentials of programming in Python 3. x including graphical user interface are also provided. The codes in the book are available for download on the book’s website. Discusses most standard topics of traditional physical and geometrical optics through Python and PyQt5 Provides visualizations and in-depth descriptions of Python’s programming language and simulations Includes simulated laboratories where students are provided a hands-on exploration of Python software Coding and programming featured within the text are available for download on the book’s corresponding website. Understanding Optics with Python by Vasudevan Lakshminarayanan Hassen Ghalila Ahmed Ammar and L. Srinivasa Varadharajan is born around a nice idea: using simulations to provide the students with a powerful tool to understand and master optical phenomena. The choice of the Python language is perfectly matched with the overall goal of the book as the Python language provides a completely free and easy-to-learn platform with huge cross-platform compatibility where the reader of the book can conduct his or her own numerical experiments to learn faster and better. — Costantino De Angelis University of Brescia Italy Teaching an important programming language like Python through concrete examples from optics is a natural and in my view very effective approach. I believe that this book will be used by students and appreciated greatly by instructors. The topic of modelling optical effects and systems where the students should already have a physical background provides great motivation for students to learn the basics of a powerful programming language without the intimidation factor that often goes with a formal computer science course. — John Dudley FEMTO-ST Institute Besançon France

GBP 130.00
1

Image Processing and Acquisition using Python

Image Processing and Acquisition using Python

Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing—one of the first books to integrate these topics together. By improving readers’ knowledge of image acquisition techniques and corresponding image processing the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn Python is used in a variety of practical examples. A refresher for more experienced readers the first part of the book presents an introduction to Python Python modules reading and writing images using Python and an introduction to images. The second part discusses the basics of image processing including pre/post processing using filters segmentation morphological operations and measurements. The second part describes image acquisition using various modalities such as x-ray CT MRI light microscopy and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry. Features Covers both the physical methods of obtaining images and the analytical processing methods required to understand the science behind the images. Contains many examples detailed derivations and working Python examples of the techniques. Offers practical tips on image acquisition and processing. Includes numerous exercises to test the reader’s skills in Python programming and image processing with solutions to selected problems example programs and images available on the book’s web page. New to this edition Machine learning has become an indispensable part of image processing and computer vision so in this new edition two new chapters are included: one on neural networks and the other on convolutional neural networks. A new chapter on affine transform and many new algorithms. Updated Python code aligned to the latest version of modules.

GBP 44.99
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