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Books on the topic 'Supervised and unsupervised machine learning'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Albalate, Amparo, and Wolfgang Minker. Semi-Supervised and Unsupervised Machine Learning. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118557693.

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2

Berry, Michael W., Azlinah Mohamed, and Bee Wah Yap, eds. Supervised and Unsupervised Learning for Data Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-22475-2.

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3

Cerulli, Giovanni. Fundamentals of Supervised Machine Learning. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-41337-7.

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4

Baruque, Bruno. Fusion methods for unsupervised learning ensembles. Springer, 2010.

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5

Vendan, S. Arungalai, Rajeev Kamal, Abhinav Karan, Liang Gao, Xiaodong Niu, and Akhil Garg. Welding and Cutting Case Studies with Supervised Machine Learning. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9382-2.

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6

H, Fisher Douglas, Pazzani Michael John 1958-, and Langley Pat, eds. Concept formation: Knowledge and experience in unsupervised learning. Morgan Kaufmann Publishers, 1991.

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7

Aldrich, Chris, and Lidia Auret. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5185-2.

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8

Aldrich, Chris. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Springer London, 2013.

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9

Jo, Taeho. Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning. Springer International Publishing AG, 2022.

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10

Jo, Taeho. Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning. Springer International Publishing AG, 2021.

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11

Colins, Michael. Machine Learning: An Introduction To Supervised & Unsupervised Learning Algorithms. Createspace Independent Publishing Platform, 2017.

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12

Sage, Anderson. Machine Learning Foundation: An Introduction to Supervised and Unsupervised Learning. Independently Published, 2022.

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13

Applications Of Supervised And Unsupervised Ensemble Methods. Springer, 2009.

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14

Okun, Oleg. Supervised and Unsupervised Ensemble Methods and Their Applications. Springer London, Limited, 2008.

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15

Okun, Oleg. Supervised and Unsupervised Ensemble Methods and their Applications. Springer, 2010.

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16

Okun, Oleg. Applications of Supervised and Unsupervised Ensemble Methods. Springer, 2009.

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17

Okun, Oleg. Applications of Supervised and Unsupervised Ensemble Methods. Springer Berlin / Heidelberg, 2012.

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18

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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19

Huang, Te-Ming, Vojislav Kecman, and Ivica Kopriva. Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-Supervised, and Unsupervised Learning. Springer London, Limited, 2006.

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20

Huang, Te-Ming, Vojislav Kecman, and Ivica Kopriva. Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning. Springer, 2010.

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21

Machine learning Beginners Guide Algorithms: Supervised & Unsupervised learning, Decision Tree & Random Forest Introduction. CreateSpace Independent Publishing Platform, 2017.

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22

Chinnamgari, Sunil Kumar. R Machine Learning Projects: Implement Supervised, Unsupervised, and Reinforcement Learning Techniques Using R 3. 5. Packt Publishing, Limited, 2019.

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23

Dangeti, Pratap. Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R. Packt Publishing, 2017.

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24

Bironneau, Michael, and Toby Coleman. Machine Learning with Go Quick Start Guide: Hands-On Techniques for Building Supervised and Unsupervised Machine Learning Workflows. Packt Publishing, Limited, 2019.

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25

Huang, Te-Ming, Vojislav Kecman, and Ivica Kopriva. Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning (Studies in Computational Intelligence). Springer, 2006.

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26

Herreros, Ivan. Learning and control. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0026.

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This chapter discusses basic concepts from control theory and machine learning to facilitate a formal understanding of animal learning and motor control. It first distinguishes between feedback and feed-forward control strategies, and later introduces the classification of machine learning applications into supervised, unsupervised, and reinforcement learning problems. Next, it links these concepts with their counterparts in the domain of the psychology of animal learning, highlighting the analogies between supervised learning and classical conditioning, reinforcement learning and operant cond

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27

FISHER, Terry. Paperback - a Practical Guide to Implementing Supervised and Unsupervised Machine Learning Algorithms in Python. Independently Published, 2021.

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28

Statistics for Machine Learning: Techniques for Exploring Supervised, Unsupervised, and Reinforcement Learning Models with Python and R. de Gruyter GmbH, Walter, 2017.

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29

Amr, Tarek. Hands-On Machine Learning with Scikit-learn and Scientific Python Toolkits: A Practical Guide to Implementing Supervised and Unsupervised Machine Learning Algorithms in Python. Packt Publishing, Limited, 2020.

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30

Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits: A practical guide to implementing supervised and unsupervised machine learning algorithms in Python. Packt Publishing, 2020.

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31

Kolosova, Tanya, and Samuel Berestizhevsky. Supervised Machine Learning. Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9780429297595.

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32

Makatjane, Katleho, and Roscoe van Wyk. Identifying structural changes in the exchange rates of South Africa as a regime-switching process. UNU-WIDER, 2020. http://dx.doi.org/10.35188/unu-wider/2020/919-8.

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Exchange rate volatility is said to exemplify the economic health of a country. Exchange rate break points (known as structural breaks) have a momentous impact on the macroeconomy of a country. Nonetheless, this country study makes use of both unsupervised and supervised machine learning algorithms to classify structural changes as regime shifts in real exchange rates in South Africa. Weekly data for the period January 2003–June 2020 are used. To these data we apply both non-linear principal component analysis and Markov-switching generalized autoregressive conditional heteroscedasticity. The

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33

Berry, Michael W., Bee Wah Yap, and Azlinah Mohamed. Supervised and Unsupervised Learning for Data Science. Springer, 2019.

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34

Berry, Michael W., Bee Wah Yap, and Azlinah Mohamed. Supervised and Unsupervised Learning for Data Science. Springer International Publishing AG, 2020.

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35

Celebi, M. Emre, and Kemal Aydin. Unsupervised Learning Algorithms. Springer London, Limited, 2016.

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36

Unsupervised Learning Algorithms. Springer, 2016.

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37

Bakshi, Elisabeth. Unsupervised Learning : Identify Machine Learning Tasks: Machine Learning Course. Independently Published, 2021.

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38

Dhoot, Dr. Supervised Machine Learning for Kids. Tinker Toddlers, 2020.

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39

Dhoot, Dr. Supervised Machine Learning for Kids. Tinker Toddlers, 2020.

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40

Unsupervised Learning with R. Packt Publishing, Limited, 2015.

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41

Unsupervised Learning with R. Packt Publishing, 2015.

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42

Marks, F. MACHINE LEARNING. SUPERVISED LEARNING TECHNIQUES Through R. Independently Published, 2020.

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43

Vidales, A. MACHINE LEARNING with MATLAB: NONPARAMETRIC SUPERVISED LEARNING. Independently Published, 2019.

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44

King, Irwin, and Zenglin Xu. Introduction to Semi-Supervised Learning. Taylor & Francis Group, 2021.

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45

Lopez, César Perez. Machine Learning with Matlab. Unsupervised Learning Techniques: Classification. Lulu Press, Inc., 2020.

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46

Perez, C. Machine Learning Techniques: UNSUPERVISED LEARNING. EXAMPLES with MATLAB. Independently Published, 2019.

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47

Goldberg, Andrew, and Xiaojin Zhu. Introduction to Semi-Supervised Learning. Morgan & Claypool Publishers, 2009.

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48

Albalate, Amparo, and Wolfgang Minker. Semi-Supervised and Unervised Machine Learning. Wiley & Sons, Incorporated, John, 2013.

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49

Smith, Taylor. Supervised Machine Learning with Python: Develop Rich Python Coding Practices While Exploring Supervised Machine Learning. Packt Publishing, Limited, 2019.

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50

Muneesawang, Paisarn, Ling Guan, Matthew Kyan, and Kambiz Jarrah. Unsupervised Learning: A Dynamic Approach. Wiley & Sons, Incorporated, John, 2014.

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