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Books on the topic 'Machine learning in education'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Bauer, James J. The runaway learning machine: Growing up dyslexic. Minneapolis, MN: Educational Media Corp., 1992.

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2

Gábor, Lugosi, ed. Prediction, learning, and games. Cambridge: Cambridge University Press, 2006.

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3

Joan, Bliss, Säljö Roger 1948-, Light Paul, and European Association for Research on Learning and Instruction, eds. Learning sites: Social and technological resources for learning. Amsterdam: Pergamon, 1999.

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4

Paul, Reid. Learning about simple machines. Niagara Falls, N.Y: T4T Learning Materials, 1998.

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5

Web-based learning: Men & machines : proceedings of the first Interational Conference on Web-Based Learning in China, ICWL, 2002, Hong Kong, 17-19 August 2002. New Jersey: World Scientific, 2002.

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6

Christian), Stephan Frank (Frank, Vovk Vladimir 1960-, Zeugmann Thomas, and SpringerLink (Online service), eds. Algorithmic Learning Theory: 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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7

Topolsky, Nikolay, and Valeriy Vilisov. Methods, models and algorithms in security systems: machine learning, robotics, insurance, risks, control. ru: Publishing Center RIOR, 2021. http://dx.doi.org/10.29039/02072-2.

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The monograph examines topical issues of decision support and management in safety systems for fire and emergency situations through the use of innovative approaches and tools for operations research, artificial intelligence, robotics and management methods in organizational systems. The monograph is intended for faculty, researchers, graduate students (adjuncts) and doctoral students, as well as for undergraduates, students and listeners of educational organizations, all those who are interested in the problems of decision support and management in security systems.

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8

1949-, Kennewell Steve, Parkinson John 1947-, and Tanner Howard 1951-, eds. Learning to teach ICT in the secondary school. London: RoutledgeFalmer, 2002.

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9

Polyakova, Anna, Tat'yana Sergeeva, and Irina Kitaeva. The continuous formation of the stochastic culture of schoolchildren in the context of the digital transformation of general education. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1876368.

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The material presented in the monograph shows the possibilities of continuous teaching of mathematics at school, namely, the significant potential of modern information and communication technologies, with the help of which it is possible to form elements of stochastic culture among students. Continuity in learning is considered from two positions: procedural and educational-cognitive. In addition, a distinctive feature of the book is the presentation of the digital transformation of general education as a way to overcome the "new digital divide". Methodological features of promising digital technologies (within the framework of teaching students the elements of the probabilistic and statistical line) that contribute to overcoming the "new digital divide": artificial intelligence, the Internet of Things, additive manufacturing, machine learning, blockchain, virtual and augmented reality are described. The solution of the main questions of probability theory and statistics in the 9th grade mathematics course is proposed to be carried out using a distance learning course built in the Moodle distance learning system. The content, structure and methodological features of the implementation of the stochastics course for students of grades 10-11 of a secondary school are based on the use of such tools in the educational process as an online calculator for plotting functions, the Wolfram Alpha service, Google Docs and Google Tables services, the Yaklass remote training, the Banktest website.<url>", interactive module "Galton Board", educational website "Mathematics at school". It will be interesting for students, undergraduates, postgraduates, mathematics teachers, as well as specialists improving their qualifications in the field of pedagogical education.

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10

David, Meister, ed. The Russian theory of activity: Current applications to design and learning. Mahwah, N.J: Lawrence Erlbaum Associates, 1997.

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11

Zhou, Zhi-Hua. Machine Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-1967-3.

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12

Jung, Alexander. Machine Learning. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8193-6.

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13

Mitchell, Tom M., Jaime G. Carbonell, and Ryszard S. Michalski. Machine Learning. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2279-5.

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14

Fernandes de Mello, Rodrigo, and Moacir Antonelli Ponti. Machine Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94989-5.

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15

Bell, Jason. Machine Learning. Indianapolis, IN, USA: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781119183464.

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16

Gulzar, Zameer, and A. Anny Leema. Machine Learning Approaches for Improvising Modern Learning Systems. IGI Global, 2020.

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17

Gulzar, Zameer, and A. Anny Leema. Machine Learning Approaches for Improvising Modern Learning Systems. IGI Global, 2020.

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18

Gulzar, Zameer, and A. Anny Leema. Machine Learning Approaches for Improvising Modern Learning Systems. IGI Global, 2020.

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19

Gulzar, Zameer, and A. Anny Leema. Machine Learning Approaches for Improvising Modern Learning Systems. IGI Global, 2020.

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20

1st, Mannanuddin Khaja, Joseph Susheel George 2nd, and Thirupathi Lingala 3rd. Machine Learning Architecture a Recent Paradigm. Selfypage Developers Pvt Ltd, 2021.

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21

1st, Deepika Nalabala, and Manda Sridhar 2nd. Concepts of Machine Learning for Absolute Beginners. INSC International Publisher (IIP), 2021.

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22

Gulzar, Zameer, and A. Anny Leema. Machine Learning Approaches for Improvising Modern Learning Systems. IGI Global, 2020.

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23

1st, Diwan Tarun Dhar. Understanding Machine Learning for Future Technology and Innovation. INSC International Publisher (IIP), 2021.

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24

Singh, Abhishek Narain. Bioinformatics: Big Data & Machine Learning in Biochemical Pathways. INSC International Publisher (IIP), 2021.

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25

Menon, Lata, Pradip P. Chatterjjee, and Prof Mange Amar Vilasrao. Analysis of a Machine Learning in Education System. Namya Press, 2022.

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26

Menon, Lata, Pradip P. Chatterjjee, and Prof Mange Amar Vilasrao. Analysis of a Machine Learning in Education System. Namya Press, 2022.

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27

Khadimally, Seda. Applications of Machine Learning and Artificial Intelligence in Education. IGI Global, 2021.

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28

Khadimally, Seda. Applications of Machine Learning and Artificial Intelligence in Education. IGI Global, 2022.

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29

Khadimally, Seda. Applications of Machine Learning and Artificial Intelligence in Education. IGI Global, 2022.

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30

Khadimally, Seda. Applications of Machine Learning and Artificial Intelligence in Education. IGI Global, 2022.

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31

Khadimally, Seda. Applications of Machine Learning and Artificial Intelligence in Education. IGI Global, 2021.

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32

Boddu, Raja Sarath Kumar. Machine Learning: A Comprehensive Practical Approach with Innovative Concepts. Selfypage Developers Pvt Ltd, 2021.

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33

Kumar, 1st Neelam Sanjeev, 2nd P. Nirmalkumar, and 3rd Kareemullah H. Feature Extraction and Classification in Context of Machine Learning. INSC International Publisher (IIP), 2021.

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34

Khadimally, Seda, ed. Applications of Machine Learning and Artificial Intelligence in Education. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7776-9.

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35

Moye, John N. Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education. Emerald Publishing Limited, 2019.

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36

Moye, John N. Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education. Emerald Publishing Limited, 2019.

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37

1st, G. Appasami, Patil Anita M. 2nd, and Bohmrah, Er. Maneet Kaur, 3rd. Data Science for Machine Learning and IoT with Health Care Application. Selfypage Developers Pvt Ltd, 2021.

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38

Moye, John N. Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education. Emerald Publishing Limited, 2019.

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39

Kshatri, 1st Sapna Singh, 2nd Devanand Bhonsle, Roshni Rahangdale Ms 3rd, Tanu Rizvi Ms IV, and V. Ruhi uzma Sheikh. Supervised and Unsupervised Machine Learning Methods and Their Crime Data Applications. INSC International Publisher (IIP), 2022.

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40

Niewiadomski, Robert, and Dennis Anderson. Revolutionizing Education in the Age of AI and Machine Learning. IGI Global, 2019.

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41

Niewiadomski, Robert, Dennis Anderson, and Maki K. Habib. Revolutionizing Education in the Age of AI and Machine Learning. IGI Global, 2019.

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42

Habib, Maki K. Revolutionizing Education in the Age of AI and Machine Learning. IGI Global, 2019.

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43

Niewiadomski, Robert, Dennis Anderson, Anderson Derek, and Maki K. Habib. Revolutionizing Education in the Age of AI and Machine Learning. IGI Global, 2019.

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44

Dhiman, Sapna, Amit Shrivastava, Susheel George Joseph, and Shweta Agrawal. Importance of Machine Learning and Artificial Intelligence for a Real-World Scenario. INSC International Publisher (IIP), 2021.

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45

Pattern Recognition and Machine Learning (Information Science and Statistics). Springer, 2008.

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46

Pazzani, Michael J., and Douglas H. Jr Fisher. Concept Formation: Knowledge and Experience in Unsupervised Learning (Morgan Kaufmann Series in Machine Learning). Morgan Kaufmann Publishers, 1991.

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47

Moye, John N. A Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education. Emerald Publishing Limited, 2019. http://dx.doi.org/10.1108/9781789738995.

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48

The Nature of Statistical Learning Theory (Information Science and Statistics). Springer, 1999.

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49

Luckin, Rosemary. Machine Learning and Human Intelligence: The Future of Education for the 21st Century. UCL IOE Press, 2018.

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50

Machina Student Learning Guide (300-day subscription). Wiley, 2002.

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