Computational Frameworks For Political And Social Research With Python
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Computational Frameworks For Political And Social Research With Python
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Author : Josh Cutler
language : en
Publisher: Springer Nature
Release Date : 2020-04-22
Computational Frameworks For Political And Social Research With Python written by Josh Cutler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-22 with Social Science categories.
This book is intended to serve as the basis for a first course in Python programming for graduate students in political science and related fields. The book introduces core concepts of software development and computer science such as basic data structures (e.g. arrays, lists, dictionaries, trees, graphs), algorithms (e.g. sorting), and analysis of computational efficiency. It then demonstrates how to apply these concepts to the field of political science by working with structured and unstructured data, querying databases, and interacting with application programming interfaces (APIs). Students will learn how to collect, manipulate, and exploit large volumes of available data and apply them to political and social research questions. They will also learn best practices from the field of software development such as version control and object-oriented programming. Instructors will be supplied with in-class example code, suggested homework assignments (with solutions), and material for practical lab sessions.
Advanced Applications Of Python Data Structures And Algorithms
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Author : Galety, Mohammad Gouse
language : en
Publisher: IGI Global
Release Date : 2023-07-05
Advanced Applications Of Python Data Structures And Algorithms written by Galety, Mohammad Gouse and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-05 with Computers categories.
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
Hands On Tinyml
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Author : Rohan Banerjee
language : en
Publisher: BPB Publications
Release Date : 2023-06-09
Hands On Tinyml written by Rohan Banerjee and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-09 with Computers categories.
Learn how to deploy complex machine learning models on single board computers, mobile phones, and microcontrollers KEY FEATURES ● Gain a comprehensive understanding of TinyML's core concepts. ● Learn how to design your own TinyML applications from the ground up. ● Explore cutting-edge models, hardware, and software platforms for developing TinyML. DESCRIPTION TinyML is an innovative technology that empowers small and resource-constrained edge devices with the capabilities of machine learning. If you're interested in deploying machine learning models directly on microcontrollers, single board computers, or mobile phones without relying on continuous cloud connectivity, this book is an ideal resource for you. The book begins with a refresher on Python, covering essential concepts and popular libraries like NumPy and Pandas. It then delves into the fundamentals of neural networks and explores the practical implementation of deep learning using TensorFlow and Keras. Furthermore, the book provides an in-depth overview of TensorFlow Lite, a specialized framework for optimizing and deploying models on edge devices. It also discusses various model optimization techniques that reduce the model size without compromising performance. As the book progresses, it offers a step-by-step guidance on creating deep learning models for object detection and face recognition specifically tailored for the Raspberry Pi. You will also be introduced to the intricacies of deploying TensorFlow Lite applications on real-world edge devices. Lastly, the book explores the exciting possibilities of using TensorFlow Lite on microcontroller units (MCUs), opening up new opportunities for deploying machine learning models on resource-constrained devices. Overall, this book serves as a valuable resource for anyone interested in harnessing the power of machine learning on edge devices. WHAT YOU WILL LEARN ● Explore different hardware and software platforms for designing TinyML. ● Create a deep learning model for object detection using the MobileNet architecture. ● Optimize large neural network models with the TensorFlow Model Optimization Toolkit. ● Explore the capabilities of TensorFlow Lite on microcontrollers. ● Build a face recognition system on a Raspberry Pi. ● Build a keyword detection system on an Arduino Nano. WHO THIS BOOK IS FOR This book is designed for undergraduate and postgraduate students in the fields of Computer Science, Artificial Intelligence, Electronics, and Electrical Engineering, including MSc and MCA programs. It is also a valuable reference for young professionals who have recently entered the industry and wish to enhance their skills. TABLE OF CONTENTS 1. Introduction to TinyML and its Applications 2. Crash Course on Python and TensorFlow Basics 3. Gearing with Deep Learning 4. Experiencing TensorFlow 5. Model Optimization Using TensorFlow 6. Deploying My First TinyML Application 7. Deep Dive into Application Deployment 8. TensorFlow Lite for Microcontrollers 9. Keyword Spotting on Microcontrollers 10. Conclusion and Further Reading Appendix
Computational Analysis Of Communication
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Author : Wouter van Atteveldt
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-02
Computational Analysis Of Communication written by Wouter van Atteveldt and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-02 with Social Science categories.
Provides clear guidance on leveraging computational techniques to answer social science questions In disciplines such as political science, sociology, psychology, and media studies, the use of computational analysis is rapidly increasing. Statistical modeling, machine learning, and other computational techniques are revolutionizing the way electoral results are predicted, social sentiment is measured, consumer interest is evaluated, and much more. Computational Analysis of Communication teaches social science students and practitioners how computational methods can be used in a broad range of applications, providing discipline-relevant examples, clear explanations, and practical guidance. Assuming little or no background in data science or computer linguistics, this accessible textbook teaches readers how to use state-of-the art computational methods to perform data-driven analyses of social science issues. A cross-disciplinary team of authors—with expertise in both the social sciences and computer science—explains how to gather and clean data, manage textual, audio-visual, and network data, conduct statistical and quantitative analysis, and interpret, summarize, and visualize the results. Offered in a unique hybrid format that integrates print, ebook, and open-access online viewing, this innovative resource: Covers the essential skills for social sciences courses on big data, data visualization, text analysis, predictive analytics, and others Integrates theory, methods, and tools to provide unified approach to the subject Includes sample code in Python and links to actual research questions and cases from social science and communication studies Discusses ethical and normative issues relevant to privacy, data ownership, and reproducible social science Developed in partnership with the International Communication Association and by the editors of Computational Communication Research Computational Analysis of Communication is an invaluable textbook and reference for students taking computational methods courses in social sciences, and for professional social scientists looking to incorporate computational methods into their work.
Elgar Encyclopedia Of Law And Data Science
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Author : Comandé, Giovanni
language : en
Publisher: Edward Elgar Publishing
Release Date : 2022-02-18
Elgar Encyclopedia Of Law And Data Science written by Comandé, Giovanni and has been published by Edward Elgar Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-18 with Law categories.
This Encyclopedia brings together jurists, computer scientists, and data analysts to map the emerging field of data science and law for the first time, uncovering the challenges, opportunities, and fault lines that arise as these groups are increasingly thrown together by expanding attempts to regulate and adapt to a data-driven world. It explains the concepts and tools at the crossroads of the many disciplines involved in data science and law, bridging scientific and applied domains. Entries span algorithmic fairness, consent, data protection, ethics, healthcare, machine learning, patents, surveillance, transparency and vulnerability.
Doing Computational Social Science
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Author : John McLevey
language : en
Publisher: SAGE
Release Date : 2021-12-15
Doing Computational Social Science written by John McLevey and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-15 with Business & Economics categories.
Computational approaches offer exciting opportunities for us to do social science differently. This beginner’s guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed. For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.
Computational Social Science
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Author : R. Michael Alvarez
language : en
Publisher: Cambridge University Press
Release Date : 2016-03-10
Computational Social Science written by R. Michael Alvarez and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-10 with Political Science categories.
This book provides an overview of cutting-edge approaches to computational social science.
Text Analysis In Python For Social Scientists
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Author : Dirk Hovy
language : en
Publisher: Cambridge University Press
Release Date : 2022-03-17
Text Analysis In Python For Social Scientists written by Dirk Hovy and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-17 with Political Science categories.
Text contains a wealth of information about about a wide variety of sociocultural constructs. Automated prediction methods can infer these quantities (sentiment analysis is probably the most well-known application). However, there is virtually no limit to the kinds of things we can predict from text: power, trust, misogyny, are all signaled in language. These algorithms easily scale to corpus sizes infeasible for manual analysis. Prediction algorithms have become steadily more powerful, especially with the advent of neural network methods. However, applying these techniques usually requires profound programming knowledge and machine learning expertise. As a result, many social scientists do not apply them. This Element provides the working social scientist with an overview of the most common methods for text classification, an intuition of their applicability, and Python code to execute them. It covers both the ethical foundations of such work as well as the emerging potential of neural network methods.
Computational Thinking And Social Science
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Author : Matti Nelimarkka
language : en
Publisher: SAGE
Release Date : 2022-12-31
Computational Thinking And Social Science written by Matti Nelimarkka and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-31 with Reference categories.
This book provides fundamental understanding into computational social science, helping students build basic familiarity with programming and an in-depth understanding into the challenges and benefits within the field.
Text As Data
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Author : Justin Grimmer
language : en
Publisher: Princeton University Press
Release Date : 2022-03-29
Text As Data written by Justin Grimmer and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-29 with Computers categories.
A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry