Data Analytics For Discourse Analysis With Python
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Data Analytics For Discourse Analysis With Python
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Author : Dennis Tay
language : en
Publisher: Taylor & Francis
Release Date : 2024-04-19
Data Analytics For Discourse Analysis With Python written by Dennis Tay and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-19 with Language Arts & Disciplines categories.
This concise volume, using examples of psychotherapy talk, showcases the potential applications of data analytics for advancing discourse research and other related disciplines. The book provides a brief primer on data analytics, defined as the science of analyzing raw data to reveal new insights and support decision making. Currently underutilized in discourse research, Tay draws on the case of psychotherapy talk, in which clients’ concerns are worked through via verbal interaction with therapists, to demonstrate how data analytics can address both practical and theoretical concerns. Each chapter follows a consistent structure, offering a streamlined walkthrough of a key technique, an example case study, and annotated Python code. The volume shows how techniques such as simulations, classification, clustering, and time series analysis can address such issues as incomplete data transcripts, therapist–client (a)synchrony, and client prognosis, offering inspiration for research, training, and practitioner self-reflection in psychotherapy and other discourse contexts. This volume is a valuable resource for discourse and linguistics researchers, particularly for those interested in complementary approaches to qualitative methods, as well as active practitioners.
Data Analytics With Python
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Author : Frank Millstein
language : en
Publisher: Frank Millstein
Release Date : 2020-05-08
Data Analytics With Python written by Frank Millstein and has been published by Frank Millstein this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Computers categories.
Data Analytics With Python Data is the foundation of this digital age that we live in. With this book, you are going to learn how to organize and analyze data and how to interpret vast sources of information. This book covers various topics on data analytics such as data analytics applications, data analytics process, using Python for data analytics, Python libraries for data analytics and many other that will help you kick-start your data analytics journey from the very beginning. In this book you are going to learn how to use Python its tools in order to interpret data and examine those interesting data trends and information, which are important in predicting the future. Whether you are dealing with some medical data, sales data, web page data, you can use Python in order to interpret data, analyze it and obtain this valuable information. You can also use this data for creating data analytics models and predictions. Here Is A Brief Preview of What You’ll Learn In This Book… -Data analytics applications -Data analytics process -How to install and run Python -Python data structures and Python libraries -Python conditional construct and iteration -Data exploration using Pandas -Pandas series and dataframes -Data munging and distribution analysis -Carrying out binary operations -Data manipulation and categorical variable analysis -How to build a predictive model -And of course much, much more! Get this book NOW and learn more about Data Analytics With Python!
Text Analytics With Python
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Author : Dipanjan Sarkar
language : en
Publisher: Apress
Release Date : 2019-05-21
Text Analytics With Python written by Dipanjan Sarkar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-21 with Computers categories.
Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.
Python Data Analytics
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Author : Fabio Nelli
language : en
Publisher: Apress
Release Date : 2015-08-25
Python Data Analytics written by Fabio Nelli and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-25 with Computers categories.
Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Author Fabio Nelli expertly shows the strength of the Python programming language when applied to processing, managing and retrieving information. Inside, you will see how intuitive and flexible it is to discover and communicate meaningful patterns of data using Python scripts, reporting systems, and data export. This book examines how to go about obtaining, processing, storing, managing and analyzing data using the Python programming language. You will use Python and other open source tools to wrangle data and tease out interesting and important trends in that data that will allow you to predict future patterns. Whether you are dealing with sales data, investment data (stocks, bonds, etc.), medical data, web page usage, or any other type of data set, Python can be used to interpret, analyze, and glean information from a pile of numbers and statistics. This book is an invaluable reference with its examples of storing and accessing data in a database; it walks you through the process of report generation; it provides three real world case studies or examples that you can take with you for your everyday analysis needs.
Coordination And The Strong Minimalist Thesis
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Author : Stefanie Bode
language : en
Publisher: Taylor & Francis
Release Date : 2024-03-27
Coordination And The Strong Minimalist Thesis written by Stefanie Bode and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-27 with Language Arts & Disciplines categories.
This book unpacks coordination in the context of the Strong Minimalist Thesis (SMT), offering a new proposal for addressing this longstanding puzzle within research on Generative Grammar. The volume’s foundations are rooted in the SMT, which builds on the idea that laws of nature, such as simplicity, symmetry, and computational efficiency, shape the laws of language to their simplest form, as units of computation combined with a recursive structure-building device. The book explores the two main ways in which Generative Grammar research has been undertaken to deal with the issue of coordination within SMT as examined in such linguistic expressions as conjuncts, which combine in an unstructured way, but which run counter to a strictly minimalist approach. Bode proposes an alternative account of coordination based on simplest set-formation without resorting to additional mechanisms, rooting it more squarely within SMT theory and encouraging further discussion on new directions for SMT-related research. This volume will be of interest to scholars in syntax and linguistic theory, particularly those interested in minimalist theory.
Independent Wh Exclamative Constructions In The History Of English
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Author : Daniela Schröder
language : en
Publisher: Taylor & Francis
Release Date : 2024-07-31
Independent Wh Exclamative Constructions In The History Of English written by Daniela Schröder and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Language Arts & Disciplines categories.
This book offers the first book-length treatment of the diachronic study of English exclamatives, tracing their development from 1500 through to the twenty-first century. The volume shines a light on independent wh-exclamatives in the history of English. In particular, Schröder calls attention to the development of three prototypical wh-exclamatives as observed in three newly created genre-balance corpora comprising prose fiction, dialogues, and personal correspondence, uncovering new insights into the differences in their evolution. In its analysis of English exclamatives over time and broader exploration of the impact of genre on constructional productivity, the book raises key questions about existing claims in scholarship on Diachronic Construction Grammar and outlines ways forward for new areas of inquiry. This volume will appeal to scholars interested in diachronic linguistics, historical syntax, language variation and change, and the history of English.
Advanced Data Analytics Using Python
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Author : Sayan Mukhopadhyay
language : en
Publisher: Apress
Release Date : 2018-03-29
Advanced Data Analytics Using Python written by Sayan Mukhopadhyay and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-29 with Computers categories.
Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis. After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects. What You Will Learn Work with data analysis techniques such as classification, clustering, regression, and forecasting Handle structured and unstructured data, ETL techniques, and different kinds of databases such as Neo4j, Elasticsearch, MongoDB, and MySQL Examine the different big data frameworks, including Hadoop and Spark Discover advanced machine learning concepts such as semi-supervised learning, deep learning, and NLP Who This Book Is For Data scientists and software developers interested in the field of data analytics.
Python For Data Analytics
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Author : Alex Root
language : en
Publisher:
Release Date : 2019-09-06
Python For Data Analytics written by Alex Root and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-06 with categories.
Learn data analysis using Python with this easy to follow beginners guide. It covers all aspects of processing, manipulation, crunching, and cleaning data using Python programming language. It has been designed to prepare you for: analyzing data creating relevant data visualizations carrying out statistical analyses for large data estimating the upcoming future trends by using current data and lots more! This book will help you learn the various parts of Python programming language, its libraries, and scientific computation using Python. Learn to practically solve extensive sets of problems related to data analysis. Python is on par with other programming languages like MATLAB, Stata, R, SAS, and others when it comes to data analysis and data visualization. Python's rich set of libraries (mainly Pandas) has grown rapidly in recent years and is considered one of the best among its competitors for tasks related to data manipulation. When combined with Python's own internal solidity, as a general purpose programming language, we can say that it is an excellent choice to build data centric web applications. You will learn how to use the essential Python libraries required for data analysis like NumPy, Pandas, matplotlib, IPython, and SciPy. Each one of them performs a particular functionality for data analysis and you will be surprised at how easy it is. So what are you waiting for? Now is your chance to learn hands on Python with ease. Click the BUY NOW button to get started on your Python journey.
Python Data Analytics
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Author : Stephen Ward
language : en
Publisher:
Release Date : 2020-10-15
Python Data Analytics written by Stephen Ward and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-15 with categories.
Unlock the programming skills you need to prepare for a lucrative career in Data Science with this comprehensive introduction to Python programming for data analytics! Are you completely new to programming and want to learn how to code, but don't know where to begin? Are you looking to upgrade your data wrangling skills to future-proof your career and break into Data Science and Analytics? If you answered yes to any of the questions above, then keep reading... Data analysis has become a huge industry with tons of career potential and will remain relevant far into the foreseeable future. With the exponential growth and explosion of new data and the focus on using data to improve customer experiences and carry out research, data analysts will be needed to process and make sense of large amounts of information, with Python being the language of choice because of its versatility. In this guide, you're going to be shown everything you need to break into the world of Data Analysis with Python. Filled with tutorials for powerful libraries and practical, hands-on exercises, you're going to learn how to aggregate, munge, analyze and visualize data in Python. Here's a sample of what you're going to discover in Python Data Analytics Why Python is the perfect language to learn if you want to break into Big Data and data analytics Core statistical models and computation methods you need to know about as a budding data analyst How to master the CSV library for reading, writing and handling tabular data Using the Xlrd library to extract data from Microsoft Excel files How to convert text to speech using the powerful Win32.com library How to use the NumPy library to carry out fundamental and basic scientific and technical computing How to use the SciPy library to carry out advanced scientific and highly technical computing Surefire ways to manipulate the easy-to-use data structures of the Pandas framework for high-performance data analysis How to plot complex data, create figures and visualize data using the Python Matplotlib library ...and tons more! If you're completely new to programming and have never written a single line of code, but want to get started, this guide is perfect for as a crash guide to getting up to speed with programming in general. Whether you're a programmer looking to switch into an exciting new field with lots of potential for the future, or a regular data analyst looking to acquire the skills needed to remain relevant in a fast-changing world, this guide will teach you how to master powerful libraries used in the real-world by experienced data scientists.
Data Analytics In Cognitive Linguistics
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Author : Dennis Tay
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-05-09
Data Analytics In Cognitive Linguistics written by Dennis Tay and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-09 with Language Arts & Disciplines categories.
Contemporary data analytics involves extracting insights from data and translating them into action. With its turn towards empirical methods and convergent data sources, cognitive linguistics is a fertile context for data analytics. There are key differences between data analytics and statistical analysis as typically conceived. Though the former requires the latter, it emphasizes the role of domain-specific knowledge. Statistical analysis also tends to be associated with preconceived hypotheses and controlled data. Data analytics, on the other hand, can help explore unstructured datasets and inspire emergent questions. This volume addresses two key aspects in data analytics for cognitive linguistic work. Firstly, it elaborates the bottom-up guiding role of data analytics in the research trajectory, and how it helps to formulate and refine questions. Secondly, it shows how data analytics can suggest concrete courses of research-based action, which is crucial for cognitive linguistics to be truly applied. The papers in this volume impart various data analytic methods and report empirical studies across different areas of research and application. They aim to benefit new and experienced researchers alike.