Text Mining Applications Using Real World Data In Python

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Text Mining Applications Using Real World Data In Python

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Author : Orhan Abar
language : tr
Publisher: Nobel Akademik Yayıncılık
Release Date :

Text Mining Applications Using Real World Data In Python written by Orhan Abar and has been published by Nobel Akademik Yayıncılık this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.

Introduction To Python Programming For Business And Social Science Applications

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Author : Frederick Kaefer
language : en
Publisher: SAGE Publications
Release Date : 2020-08-06

Introduction To Python Programming For Business And Social Science Applications written by Frederick Kaefer and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-06 with Business & Economics categories.

Would you like to gather big datasets, analyze them, and visualize the results, all in one program? If this describes you, then Introduction to Python Programming for Business and Social Science Applications is the book for you. Authors Frederick Kaefer and Paul Kaefer walk you through each step of the Python package installation and analysis process, with frequent exercises throughout so you can immediately try out the functions you’ve learned. Written in straightforward language for those with no programming background, this book will teach you how to use Python for your research and data analysis. Instead of teaching you the principles and practices of programming as a whole, this application-oriented text focuses on only what you need to know to research and answer social science questions. The text features two types of examples, one set from the General Social Survey and one set from a large taxi trip dataset from a major metropolitan area, to help readers understand the possibilities of working with Python. Chapters on installing and working within a programming environment, basic skills, and necessary commands will get you up and running quickly, while chapters on programming logic, data input and output, and data frames help you establish the basic framework for conducting analyses. Further chapters on web scraping, statistical analysis, machine learning, and data visualization help you apply your skills to your research. More advanced information on developing graphical user interfaces (GUIs) help you create functional data products using Python to inform general users of data who don’t work within Python. First there was IBM® SPSS®, then there was R, and now there′s Python. Statistical software is getting more aggressive - let authors Frederick Kaefer and Paul Kaefer help you tame it with Introduction to Python Programming for Business and Social Science Applications.

Innovative Applications Of Big Data In The Railway Industry

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Author : Kohli, Shruti
language : en
Publisher: IGI Global
Release Date : 2017-11-30

Innovative Applications Of Big Data In The Railway Industry written by Kohli, Shruti and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Computers categories.

Use of big data has proven to be beneficial within many different industries, especially in the field of engineering; however, infiltration of this type of technology into more traditional heavy industries, such as the railways, has been limited. Innovative Applications of Big Data in the Railway Industry is a pivotal reference source for the latest research findings on the utilization of data sets in the railway industry. Featuring extensive coverage on relevant areas such as driver support systems, railway safety management, and obstacle detection, this publication is an ideal resource for transportation planners, engineers, policymakers, and graduate-level engineering students seeking current research on a specific application of big data and its effects on transportation.

Data Science Concepts And Techniques With Applications

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Author : Usman Qamar
language : en
Publisher: Springer Nature
Release Date : 2023-04-02

Data Science Concepts And Techniques With Applications written by Usman Qamar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-02 with Computers categories.

This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book. This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics. "This book delivers a systematic, carefully thoughtful material on Data Science." from the Foreword by Witold Pedrycz, U Alberta, Canada.

Modern Methods For Ai Integrated Language Curriculum

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Author : Jomaa, Nayef
language : en
Publisher: IGI Global
Release Date : 2025-04-25

Modern Methods For Ai Integrated Language Curriculum written by Jomaa, Nayef and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Education categories.

In today’s modern educational system, the integration of AI in language instruction transforms traditional curriculum. Innovative strategies for AI have become a part of the language learning curriculum and help personalize student experiences and support educators by creating a more adaptive teaching environment. By combining linguistic theory with cutting-edge technology, this framework redefines how learners engage with language in both digital and real-world contexts, paving the way for more dynamic, inclusive, and effective language education. Modern Methods for AI-Integrated Language Curriculum explores the use of AI in teaching and language learning. It examines current practices and new strategies in AI integration into language learning curriculum, and possible challenges. This book covers topics such as artificial intelligence, curriculum development, and education technology, and is a useful resource for educators, academicians, computer engineers, and researchers.

New Trends In Databases And Information Systems

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Author : András Benczúr
language : en
Publisher: Springer
Release Date : 2018-08-30

New Trends In Databases And Information Systems written by András Benczúr and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-30 with Computers categories.

This book constitutes the thoroughly refereed short papers, workshops and doctoral consortium papers of the 22th European Conference on Advances in Databases and Information Systems, ADBIS 2018, held in Budapest, Hungary, in September 2018. The 20 full and the 4 short workshop papers as well as the 3 doctoral consortium papers were carefully reviewed and selected from 54 submissions to the workshops and 6 submissions to the doctoral consortium. Furthermore, there are 10 short papers included, which were accepted for the main conference. The papers are organized according to the 6 workshops and the doctoral consortium: ADBIS 2018 short papers; First Workshop on Advances on Big Data Management, Analytics, Data Privacy and Security, BigDataMAPS 2018; First International Workshop on New Frontiers on Meta-data Management and Usage, M2U 2018; First Citizen Science Applications and Citizen Databases Workshop, CSADB 2018; First International Workshop on Articial Intelligence for Question Answering, AI*QA 2018; First International Workshop on BIG Data Storage, Processing and Mining for Personalized MEDicine, BIGPMED 2018; First Workshop on Current Trends in Contemporary Information Systems and Their Architectures, ISTREND 2018; Doctoral Consortium.

Introduction To Data Mining And Analytics

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Author : Kris Jamsa
language : en
Publisher: Jones & Bartlett Learning
Release Date : 2020-02-03

Introduction To Data Mining And Analytics written by Kris Jamsa and has been published by Jones & Bartlett Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-03 with Computers categories.

Data Mining and Analytics provides a broad and interactive overview of a rapidly growing field. The exponentially increasing rate at which data is generated creates a corresponding need for professionals who can effectively handle its storage, analysis, and translation.

Proceedings Of Eighth International Congress On Information And Communication Technology

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Author : Xin-She Yang
language : en
Publisher: Springer Nature
Release Date : 2023-07-25

Proceedings Of Eighth International Congress On Information And Communication Technology written by Xin-She Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-25 with Technology & Engineering categories.

This book gathers selected high-quality research papers presented at the Eighth International Congress on Information and Communication Technology, held at Brunel University, London, on 20–23 February 2023. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of Things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The work is presented in four volumes.

Python For Programmers

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Author : Paul Deitel
language : en
Publisher: Prentice Hall
Release Date : 2019-03-15

Python For Programmers written by Paul Deitel and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Computers categories.

The professional programmer’s Deitel® guide to Python® with introductory artificial intelligence case studies Written for programmers with a background in another high-level language, Python for Programmers uses hands-on instruction to teach today’s most compelling, leading-edge computing technologies and programming in Python–one of the world’s most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. In the context of 500+, real-world examples ranging from individual snippets to 40 large scripts and full implementation case studies, you’ll use the interactive IPython interpreter with code in Jupyter Notebooks to quickly master the latest Python coding idioms. After covering Python Chapters 1-5 and a few key parts of Chapters 6-7, you’ll be able to handle significant portions of the hands-on introductory AI case studies in Chapters 11-16, which are loaded with cool, powerful, contemporary examples. These include natural language processing, data mining Twitter® for sentiment analysis, cognitive computing with IBM® WatsonTM, supervised machine learning with classification and regression, unsupervised machine learning with clustering, computer vision through deep learning and convolutional neural networks, deep learning with recurrent neural networks, big data with Hadoop®, SparkTM and NoSQL databases, the Internet of Things and more. You’ll also work directly or indirectly with cloud-based services, including Twitter, Google TranslateTM, IBM Watson, Microsoft® Azure®, OpenMapQuest, PubNub and more. Features 500+ hands-on, real-world, live-code examples from snippets to case studies IPython + code in Jupyter® Notebooks Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions Procedural, functional-style and object-oriented programming Collections: Lists, tuples, dictionaries, sets, NumPy arrays, pandas Series & DataFrames Static, dynamic and interactive visualizations Data experiences with real-world datasets and data sources Intro to Data Science sections: AI, basic stats, simulation, animation, random variables, data wrangling, regression AI, big data and cloud data science case studies: NLP, data mining Twitter®, IBM® WatsonTM, machine learning, deep learning, computer vision, Hadoop®, SparkTM, NoSQL, IoT Open-source libraries: NumPy, pandas, Matplotlib, Seaborn, Folium, SciPy, NLTK, TextBlob, spaCy, Textatistic, Tweepy, scikit-learn®, Keras and more Accompanying code examples are available here: http://ptgmedia.pearsoncmg.com/imprint_downloads/informit/bookreg/9780135224335/9780135224335_examples.zip. Register your product for convenient access to downloads, updates, and/or corrections as they become available. See inside book for more information.

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.