<doi_batch xmlns="http://www.crossref.org/schema/4.4.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" version="4.4.0"><head><doi_batch_id>d3a81704-ebf7-49f9-b6eb-e04c5cacf110</doi_batch_id><timestamp>20240625082825284</timestamp><depositor><depositor_name>wseas:wseas</depositor_name><email_address>mdt@crossref.org</email_address></depositor><registrant>MDT Deposit</registrant></head><body><journal><journal_metadata language="en"><full_title>WSEAS TRANSACTIONS ON ADVANCES in ENGINEERING EDUCATION</full_title><issn media_type="electronic">2224-3410</issn><issn media_type="print">1790-1979</issn><archive_locations><archive name="Portico"/></archive_locations><doi_data><doi>10.37394/232010</doi><resource>http://wseas.org/wseas/cms.action?id=4001</resource></doi_data></journal_metadata><journal_issue><publication_date media_type="online"><month>3</month><day>26</day><year>2024</year></publication_date><publication_date media_type="print"><month>3</month><day>26</day><year>2024</year></publication_date><journal_volume><volume>21</volume><doi_data><doi>10.37394/232010.2024.21</doi><resource>https://wseas.com/journals/education/2024.php</resource></doi_data></journal_volume></journal_issue><journal_article language="en"><titles><title>Teaching Machine Learning and Deep Learning Introduction: An Innovative Tutorial-Based Practical Approach</title></titles><contributors><person_name sequence="first" contributor_role="author"><given_name>M.</given_name><surname>Sabrigiriraj</surname><affiliation>Department of Information Technology, Hindusthan College of Engineering and Technology, Coimbatore, INDIA</affiliation></person_name><person_name sequence="additional" contributor_role="author"><given_name>K.</given_name><surname>Manoharan</surname><affiliation>Department of ECE, SNS College of Technology, Coimbatore, INDIA</affiliation></person_name></contributors><jats:abstract xmlns:jats="http://www.ncbi.nlm.nih.gov/JATS1"><jats:p>Machine learning and deep learning techniques have penetrated deep into the various domains of engineering, science, and technology. They are very powerful tools to solve a wide variety of complex problems in those domains. This paper presents an innovative tutorial with practical examples of teaching the introduction to machine learning and deep learning. Starting with the basic concepts, the tutorial takes the readers through the basics of linear regression, logistic regression, and deep neural networks. Then the fundamental association between linear regression, logistic regression, and deep neural network is revealed using the practical examples. This tutorial article provides a solid base for readers aspiring to learn machine learning and deep learning with a systematic and practical approach.</jats:p></jats:abstract><publication_date media_type="online"><month>6</month><day>25</day><year>2024</year></publication_date><publication_date media_type="print"><month>6</month><day>25</day><year>2024</year></publication_date><pages><first_page>54</first_page><last_page>61</last_page></pages><publisher_item><item_number item_number_type="article_number">8</item_number></publisher_item><ai:program xmlns:ai="http://www.crossref.org/AccessIndicators.xsd" name="AccessIndicators"><ai:free_to_read start_date="2024-06-25"/><ai:license_ref applies_to="am" start_date="2024-06-25">https://wseas.com/journals/education/2024/a165110-005(2O24).pdf</ai:license_ref></ai:program><archive_locations><archive name="Portico"/></archive_locations><doi_data><doi>10.37394/232010.2024.21.8</doi><resource>https://wseas.com/journals/education/2024/a165110-005(2O24).pdf</resource></doi_data><citation_list><citation key="ref0"><doi>10.1145/3533378</doi><unstructured_citation>Paleyes, Andrei, Raoul-Gabriel Urma, and Neil D. 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