Machine learning based approaches (12 Ergebnisse)

Taschenbuch. Zustand: Neu. Query Based Text Summarization using Machine learning Approach | Learning Approaches | Zarah Zainab (u. a.) | Taschenbuch | 80 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139452828 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Emotions Detection in Music Lyrics | Using Machine Learning and Keyword-Based Approaches | Ricardo Malheiro | Taschenbuch | Englisch | 2018 | Novas Edições Acadêmicas | EAN 9786202188548 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Extraction of relevant information on a specific query from rapidly growing data is a concern for quiet time in order to scan and analyze data from all the related documents. Therefore, text summarization is paramount research area these days. It is about to find most relevant information from single or multi-documents. A reasonable amount of work is done in this area to overcome extensive searching and to reduce the time required. The knowledge-based and machine learning are the two methods for query-based text summarization where Machine learning approaches are mostly used for calculating probabilistic feature using Natural Language Processing (NLP) tools and techniques for both supervised and unsupervised learning. In the first part of this research work include to identify and analyze machine learning approaches for query-based text summarization for finding a useful summary for the users as specified by their need. In the second part, a comprehensive discussion is done to present the internal working mechanism of machine learning approaches for query-based text summarization.…

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Extraction of relevant information on a specific query from rapidly growing data is a concern for quiet time in order to scan and analyze data from all the related documents. Therefore, text summarization is paramount research area these days. It is about to find most relevant information from single or multi-documents. A reasonable amount of work is done in this area to overcome extensive searching and to reduce the time required. The knowledge-based and machine learning are the two methods for query-based text summarization where Machine learning approaches are mostly used for calculating probabilistic feature using Natural Language Processing (NLP) tools and techniques for both supervised and unsupervised learning. In the first part of this research work include to identify and analyze machine learning approaches for query-based text summarization for finding a useful summary for the users as specified by their need. In the second part, a comprehensive discussion is done to present the internal working mechanism of machine learning approaches for query-based text summarization.…

Zustand: New.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. Anirban Mukherjee has a Bachelors in Civil Engineering (1994) from Jadavpur University, Kolkata and PhD from Indian Institute of Engineering, Science and Technology (IIEST), Shibpur, India. He has been a Professor in the Department of Information .

Buch. Zustand: Neu. Neuware - The use of intelligent technologies to enhance instruction and learning is introduced in pedagogy-based learning-teaching perspective. It covers digital library resources, AI-based tools, data analysis techniques, and NLP and NLU-powered smart assistants. Students will realize their improved efficacy through use of expandable AI systems improve educational efficiency, automate repetitive chores, and enable personalized learning. The course offers useful skills for implementing contemporary AI methods in educational institutions, classrooms, and online learning settings.This book provides concise summary of forthcoming Intelligent Tools and Techniques that are using AI-based Learning-Teaching systems to shape contemporary education. It describes how NLP and NLU applications enhance intelligent teaching assistants, showcases sophisticated library resources for promoting informal learning. The book delivers a succinct but thorough approach for implementing scalable, effective, intelligent solutions that improve learning environments across a variety of educational settings through focused insights into educational data analysis and frameworks for expandable AI.Teachers, researchers, and students who wish to apply intelligent technology in the classroom are the target audience for this book. It works well for developers making intelligent learning tools, librarians overseeing digital resources, and educators investigating AI-based approaches. The book provides clear instructions on using AI, data analysis, and intelligent systems to enhance teaching, learning, and educational resource management, which will be beneficial to academic institutions, policymakers, and EdTech experts.Key features: - Contains applications of machine learning in performance analysis of students, which is helpful in designing rubrics for accreditation. - Deals with comparative study about outcome-based education and conventional educational system through application of statistical techniques. - Analyses role of emotional intelligence in measuring holistic performance of students - Evaluates different pedagogical approaches like active, authenticate, flipped, blended learning using neural network approaches. - Proposes different mathematical models for implementation of OBE for technical Institutions.…

Zustand: Good.

Hardcover. Zustand: Brand New. 268 pages. 9.18x6.12x9.21 inches. In Stock.

Zustand: gut. Machine Vision Inspection Systems: Volume 2: Machine Learning-Based Approaches In englischer Sprache. pages.