Sentiment Analysis Of Music Using Statistics And Machine Learning

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Sentiment Analysis of Music using Statistics and Machine Learning

Author : Aakash Mukherjee
Publisher : Sanctum Books
ISBN 13 : 8195293174
Total Pages : 78 pages
Book Rating : 4.1/5 (952 download)

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Book Synopsis Sentiment Analysis of Music using Statistics and Machine Learning by : Aakash Mukherjee

Download or read book Sentiment Analysis of Music using Statistics and Machine Learning written by Aakash Mukherjee and published by Sanctum Books. This book was released on 2022-10-16 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa.

Music Data Mining

Author : Tao Li
Publisher : CRC Press
ISBN 13 : 1439835551
Total Pages : 372 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Music Data Mining by : Tao Li

Download or read book Music Data Mining written by Tao Li and published by CRC Press. This book was released on 2011-07-12 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to

Cognitive Analytics: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1799824616
Total Pages : 1961 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Cognitive Analytics: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Cognitive Analytics: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-03-06 with total page 1961 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.

Statistical Analysis of Folk Songs of Jharkhand

Author : Shivani Tiwari
Publisher : Sanctum Books
ISBN 13 : 8195293166
Total Pages : 66 pages
Book Rating : 4.1/5 (952 download)

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Book Synopsis Statistical Analysis of Folk Songs of Jharkhand by : Shivani Tiwari

Download or read book Statistical Analysis of Folk Songs of Jharkhand written by Shivani Tiwari and published by Sanctum Books. This book was released on 2022-10-16 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Folk songs play a very significant role in Indian classical music as the root of Indian classical music is the Indian folk music itself. Different states have different folk songs. This work deals with the statistical analysis of the folk songs of Jharkhand. Each song's analysis concerns with verifying whether the probabilities of notes in the song are fixed throughout the song or are the note probabilities varying. This tells us whether the probability distribution followed by the notes is multinomial or quasi multinomial respectively. Statistical parameterization method is used to quantify melody and rhythm. The presence of rhythm and melody is also analyzed by the Inter Onset Interval (IOI) and note duration graphs. The book should be found useful by music researchers and students of music and musicology, ethnomusicologists and music enthusiasts.

Machine Learning and Music Generation

Author : José M. Iñesta
Publisher : Routledge
ISBN 13 : 1351234536
Total Pages : 112 pages
Book Rating : 4.3/5 (512 download)

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Book Synopsis Machine Learning and Music Generation by : José M. Iñesta

Download or read book Machine Learning and Music Generation written by José M. Iñesta and published by Routledge. This book was released on 2018-10-16 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.

Music Data Analysis

Author : Claus Weihs
Publisher : CRC Press
ISBN 13 : 1315353830
Total Pages : 716 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Music Data Analysis by : Claus Weihs

Download or read book Music Data Analysis written by Claus Weihs and published by CRC Press. This book was released on 2016-11-17 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.

Machine Learning Techniques for Text

Author : Nikos Tsourakis
Publisher : Packt Publishing Ltd
ISBN 13 : 1803236299
Total Pages : 448 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Machine Learning Techniques for Text by : Nikos Tsourakis

Download or read book Machine Learning Techniques for Text written by Nikos Tsourakis and published by Packt Publishing Ltd. This book was released on 2022-10-31 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your Python text processing skills to another level by learning about the latest natural language processing and machine learning techniques with this full color guide Key FeaturesLearn how to acquire and process textual data and visualize the key findingsObtain deeper insight into the most commonly used algorithms and techniques and understand their tradeoffsImplement models for solving real-world problems and evaluate their performanceBook Description With the ever-increasing demand for machine learning and programming professionals, it's prime time to invest in the field. This book will help you in this endeavor, focusing specifically on text data and human language by steering a middle path among the various textbooks that present complicated theoretical concepts or focus disproportionately on Python code. A good metaphor this work builds upon is the relationship between an experienced craftsperson and their trainee. Based on the current problem, the former picks a tool from the toolbox, explains its utility, and puts it into action. This approach will help you to identify at least one practical use for each method or technique presented. The content unfolds in ten chapters, each discussing one specific case study. For this reason, the book is solution-oriented. It's accompanied by Python code in the form of Jupyter notebooks to help you obtain hands-on experience. A recurring pattern in the chapters of this book is helping you get some intuition on the data and then implement and contrast various solutions. By the end of this book, you'll be able to understand and apply various techniques with Python for text preprocessing, text representation, dimensionality reduction, machine learning, language modeling, visualization, and evaluation. What you will learnUnderstand fundamental concepts of machine learning for textDiscover how text data can be represented and build language modelsPerform exploratory data analysis on text corporaUse text preprocessing techniques and understand their trade-offsApply dimensionality reduction for visualization and classificationIncorporate and fine-tune algorithms and models for machine learningEvaluate the performance of the implemented systemsKnow the tools for retrieving text data and visualizing the machine learning workflowWho this book is for This book is for professionals in the area of computer science, programming, data science, informatics, business analytics, statistics, language technology, and more who aim for a gentle career shift in machine learning for text. Students in relevant disciplines that seek a textbook in the field will benefit from the practical aspects of the content and how the theory is presented. Finally, professors teaching a similar course will be able to pick pertinent topics in terms of content and difficulty. Beginner-level knowledge of Python programming is needed to get started with this book.

Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017

Author : Fernando De la Prieta
Publisher : Springer
ISBN 13 : 3319615785
Total Pages : 350 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017 by : Fernando De la Prieta

Download or read book Trends in Cyber-Physical Multi-Agent Systems. The PAAMS Collection - 15th International Conference, PAAMS 2017 written by Fernando De la Prieta and published by Springer. This book was released on 2017-07-13 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an evolution of the International Workshop on Practical Applications of Agents and Multi-Agent Systems. PAAMS is an international yearly tribune to present, to discuss, and to disseminate the latest developments and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2017 in the special sessions: Agent-Based Social Simulation, Modelling and Big-Data Analytics (ABM); Advances on Demand Response and Renewable Energy Sources in Agent Based Smart Grids (ADRESS); Agents and Mobile Devices (AM); Computer vision in Multi-Agent Robotics (RV); Persuasive Technologies (PT); Web and Social Media Mining (WASMM). The volume also includes the papers accepted for publication in the Doctoral Consortium (DCAI, DCAI-DECON, ISAMI, MIS4TEL, PAAMS, PACBB 2017 conferences).

Sentiment Analysis

Author : Bing Liu
Publisher : Cambridge University Press
ISBN 13 : 1108787282
Total Pages : 451 pages
Book Rating : 4.1/5 (87 download)

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Book Synopsis Sentiment Analysis by : Bing Liu

Download or read book Sentiment Analysis written by Bing Liu and published by Cambridge University Press. This book was released on 2020-10-15 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.

Deep Learning-Based Approaches for Sentiment Analysis

Author : Basant Agarwal
Publisher : Springer Nature
ISBN 13 : 9811512167
Total Pages : 326 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Deep Learning-Based Approaches for Sentiment Analysis by : Basant Agarwal

Download or read book Deep Learning-Based Approaches for Sentiment Analysis written by Basant Agarwal and published by Springer Nature. This book was released on 2020-01-24 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field.

Data Science

Author : Xiaohui Cheng
Publisher : Springer Nature
ISBN 13 : 9811501181
Total Pages : 703 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Data Science by : Xiaohui Cheng

Download or read book Data Science written by Xiaohui Cheng and published by Springer Nature. This book was released on 2019-09-13 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set (CCIS 1058 and 1059) constitutes the refereed proceedings of the 5th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2019 held in Guilin, China, in September 2019. The 104 revised full papers presented in these two volumes were carefully reviewed and selected from 395 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including data mining; data base; net work; security; machine learning; bioinformatics; natural language processing; software engineering; graphic images; system; education; application.

Data Analytics with Artificial Intelligence: Transforming Big Data into Valuable Information

Author : Mehmet Ali Yilbasi
Publisher : Mehmet Ali Yılbaşı
ISBN 13 :
Total Pages : 144 pages
Book Rating : 4./5 ( download)

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Book Synopsis Data Analytics with Artificial Intelligence: Transforming Big Data into Valuable Information by : Mehmet Ali Yilbasi

Download or read book Data Analytics with Artificial Intelligence: Transforming Big Data into Valuable Information written by Mehmet Ali Yilbasi and published by Mehmet Ali Yılbaşı. This book was released on 2023-06-11 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This ebook is a guide for anyone who wants to understand the impact of Data Analytics and Artificial Intelligence in business and explore how these technologies can be applied. Businesses should use this association correctly to extract more valuable information from large data sets, optimize their operational processes and gain competitive advantage. Throughout our book, we will try to explain the potential in Data Analytics and Artificial Intelligence with examples, practical tips and real-world applications. We will also provide resources and recommendations for our readers who want to follow developments in these areas.

Music Emotion Recognition

Author : Yi-Hsuan Yang
Publisher : CRC Press
ISBN 13 : 143985047X
Total Pages : 251 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Music Emotion Recognition by : Yi-Hsuan Yang

Download or read book Music Emotion Recognition written by Yi-Hsuan Yang and published by CRC Press. This book was released on 2011-02-22 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with

Data Intelligence and Cognitive Informatics

Author : I. Jeena Jacob
Publisher : Springer Nature
ISBN 13 : 9811664609
Total Pages : 843 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Data Intelligence and Cognitive Informatics by : I. Jeena Jacob

Download or read book Data Intelligence and Cognitive Informatics written by I. Jeena Jacob and published by Springer Nature. This book was released on 2022-02-01 with total page 843 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2021), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during July 16–17, 2021. This book discusses new cognitive informatics tools, algorithms, and methods that mimic the mechanisms of the human brain which leads to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning, and cognitive science to study and develop a deeper understanding of the information processing systems.

Intelligent and Fuzzy Systems

Author : Cengiz Kahraman
Publisher : Springer Nature
ISBN 13 : 3031397770
Total Pages : 795 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Intelligent and Fuzzy Systems by : Cengiz Kahraman

Download or read book Intelligent and Fuzzy Systems written by Cengiz Kahraman and published by Springer Nature. This book was released on 2023-08-16 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of the papers accepted after a careful review process at an international scientific meeting where the latest developments on intelligent and fuzzy systems are presented and discussed. The latest developments in both the theoretical and practical fields of the new fuzzy set extensions have been prepared by expert researchers. Contributed by participants from more than 40 different countries, this book is also a useful resource in terms of showing the levels that fuzzy and intelligent systems have reached in various countries of the world. The intended readers are intelligent and fuzzy systems researchers, lecturers, M.Sc., and Ph.D. students studying fuzzy sets and artificial intelligence. The book covers fuzzy logic theory and applications, heuristics, and metaheuristics from optimization to machine learning, from quality management to risk management, making the book an excellent source for researchers.

Data Labeling in Machine Learning with Python

Author : Vijaya Kumar Suda
Publisher : Packt Publishing Ltd
ISBN 13 : 1804613789
Total Pages : 398 pages
Book Rating : 4.8/5 (46 download)

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Book Synopsis Data Labeling in Machine Learning with Python by : Vijaya Kumar Suda

Download or read book Data Labeling in Machine Learning with Python written by Vijaya Kumar Suda and published by Packt Publishing Ltd. This book was released on 2024-01-31 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.

Supervised Machine Learning for Text Analysis in R

Author : Emil Hvitfeldt
Publisher : CRC Press
ISBN 13 : 1000461971
Total Pages : 402 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Supervised Machine Learning for Text Analysis in R by : Emil Hvitfeldt

Download or read book Supervised Machine Learning for Text Analysis in R written by Emil Hvitfeldt and published by CRC Press. This book was released on 2021-10-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.