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Author: John Essick
Publisher: Oxford University Press
ISBN: 0198897006
Category : Technology & Engineering
Languages : en
Pages : 433
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Book Description
The Python-Based Laboratory: A Hands-On Guide for Scientists and Engineers provides a learn-by-doing approach to acquiring the Python programming skills needed to implement computer-controlled experimental work. The book leads its readers to mastery of the popular, open-source Python computer language in its role as a powerful laboratory tool by carrying out interesting and relevant projects that explore the acquisition, production, analysis, and presentation of digitized waveforms. Readers, who are assumed to have no prior computer programming or Python background, begin writing meaningful programs in the first few pages. The Python-Based Laboratory can be used as a textbook for science and engineering instructional laboratory students who are being taught up-to-date Python-based experimental skills. The book also works well as a self-study guide for professional laboratory researchers, industrial engineers, hobbyists, and electronics enthusiasts seeking to automate tasks using Python. Topics covered include the control of data acquisition devices (including multifunction data acquisition hardware and IEEE-interfaced stand-alone instruments), data file storage and presentation, digitized data concepts (such as resolution, sampling frequency, and aliasing), and data analysis techniques (curve fitting and fast Fourier transform). As readers work their way through the book, they build several computer-based instruments, including a DC voltmeter, digital oscilloscope, DC voltage source, waveform generator, blinking LED array, digital thermometer, and spectrum analyzer. Each chapter concludes with a Do-It-Yourself project and a Use It! example as well as a healthy selection of homework-style problems, allowing readers to test their understanding and further develop their Python-based experimentation skills.
Author: John Essick
Publisher: Oxford University Press
ISBN: 0198897006
Category : Technology & Engineering
Languages : en
Pages : 433
Get Book Here
Book Description
The Python-Based Laboratory: A Hands-On Guide for Scientists and Engineers provides a learn-by-doing approach to acquiring the Python programming skills needed to implement computer-controlled experimental work. The book leads its readers to mastery of the popular, open-source Python computer language in its role as a powerful laboratory tool by carrying out interesting and relevant projects that explore the acquisition, production, analysis, and presentation of digitized waveforms. Readers, who are assumed to have no prior computer programming or Python background, begin writing meaningful programs in the first few pages. The Python-Based Laboratory can be used as a textbook for science and engineering instructional laboratory students who are being taught up-to-date Python-based experimental skills. The book also works well as a self-study guide for professional laboratory researchers, industrial engineers, hobbyists, and electronics enthusiasts seeking to automate tasks using Python. Topics covered include the control of data acquisition devices (including multifunction data acquisition hardware and IEEE-interfaced stand-alone instruments), data file storage and presentation, digitized data concepts (such as resolution, sampling frequency, and aliasing), and data analysis techniques (curve fitting and fast Fourier transform). As readers work their way through the book, they build several computer-based instruments, including a DC voltmeter, digital oscilloscope, DC voltage source, waveform generator, blinking LED array, digital thermometer, and spectrum analyzer. Each chapter concludes with a Do-It-Yourself project and a Use It! example as well as a healthy selection of homework-style problems, allowing readers to test their understanding and further develop their Python-based experimentation skills.
Author: Aquiles Carattino
Publisher:
ISBN: 9781716517686
Category :
Languages : en
Pages : 190
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Book Description
Python for the Lab is the first book covering how to develop instrumentation software. It is ideal for researchers willing to automatize their setups and bring their experiments to the next level. The book is the product of countless workshops at different universities, and a carefully design pedagogical strategy. With an easy to follow and task-oriented design, the book uncovers all the best practices in the field. It also shows how to design code for long-term maintainability, opening the doors of fruitful collaboration among researchers from different labs.
Author: Margo L. Mankus
Publisher:
ISBN:
Category : Calculator-Based Laboratory System
Languages : en
Pages : 358
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Book Description
Author: C.C. Ko
Publisher: Springer Science & Business Media
ISBN: 9781852338374
Category : Computers
Languages : en
Pages : 392
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Book Description
Covers the transmission of real-time video and audio for internet experimentation. Provides detailed descriptions of how the various hardware and software systems can be seamlessly integrated for a complete internet remote experimentation system. Contains examples of real working experiments that are currently running.
Author: Andri M. Gretarsson
Publisher: Cambridge University Press
ISBN: 1108488854
Category : Science
Languages : en
Pages : 229
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Book Description
Learn the essential skills of laboratory optics and its underlying theoretical framework with seven key experiments.
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 609
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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617
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Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Author: Abd-Alhameed Raed
Publisher: European Alliance for Innovation
ISBN: 1631903403
Category : Social Science
Languages : en
Pages : 1790
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Book Description
This book contains the proceedings of the Second International Conference on Integrated Sciences and Technologies (IMDC-IST-2021). Where held on 7th–9th Sep 2021 in Sakarya, Turkey. This conference was organized by University of Bradford, UK and Southern Technical University, Iraq. The papers in this conference were collected in a proceedings book entitled: Proceedings of the second edition of the International Multi-Disciplinary Conference Theme: “Integrated Sciences and Technologies” (IMDC-IST-2021). The presentation of such a multi-discipline conference provides a lot of exciting insights and new understanding on recent issues in terms of Green Energy, Digital Health, Blended Learning, Big Data, Meta-material, Artificial-Intelligence powered applications, Cognitive Communications, Image Processing, Health Technologies, 5G Communications. Referring to the argument, this conference would serve as a valuable reference for future relevant research activities. The committee acknowledges that the success of this conference are closely intertwined by the contributions from various stakeholders. As being such, we would like to express our heartfelt appreciation to the keynote speakers, invited speakers, paper presenters, and participants for their enthusiastic support in joining the second edition of the International Multi-Disciplinary Conference Theme: “Integrated Sciences and Technologies” (IMDC-IST-2021). We are convinced that the contents of the study from various papers are not only encouraged productive discussion among presenters and participants but also motivate further research in the relevant subject. We appreciate for your enthusiasm to attend our conference and share your knowledge and experience. Your input was important in ensuring the success of our conference. Finally, we hope that this conference serves as a forum for learning in building togetherness and academic networks. Therefore, we expect to see you all at the next IMDC-IST.
Author: Thomas Holton
Publisher: Cambridge University Press
ISBN: 1108418449
Category : Computers
Languages : en
Pages : 1061
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Book Description
A comprehensive and mathematically accessible introduction to digital signal processing, covering theory, advanced topics, and applications.
Author: Arshdeep Bahga
Publisher: Vijay Madisetti
ISBN:
Category : Computers
Languages : en
Pages : 191
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Book Description
In response to requests for instructional and training material from instructors, we prepared this laboratory training guide as a companion book to the Cloud Computing: A Hands-On Approach ("Cloud Book"). This book is designed to serve two purposes. First, it provides a tutorial for the laboratory training that can accompany traditional or online instruction using the Cloud Book. Second, it provides access to the complete source code used in the examples provided in the Cloud Book. The authors hope that this laboratory training guide will continue to prove useful to instructors and students using the Cloud Book.
