Home »
Academic Articles & Research Papers
Showing 20 of 781 academic articles
Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong • Cambridge University Press eBooks
(2020)
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in d...
OPENALEX
DOI: https://doi.org/10.1017/9781108679930
Steven L. Brunton, J. Nathan Kutz • Cambridge University Press eBooks
(2022)
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering...
OPENALEX
DOI: https://doi.org/10.1017/9781009089517.019
Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar • The MIT Press eBooks
(2018)
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference fo...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.7551/mitpress/10290.001.0001
Michael Paluszek, Stephanie J. Thomas • Apress eBooks
(2016)
This book is a comprehensive guide to machine learning with worked examples in MATLAB. It starts with an overview of the history of Artificial Intelligence and automatic control and how the field of machine learning grew from these. It prov...
OPENALEX
DOI: https://doi.org/10.1007/978-1-4842-2250-8
Shai Shalev‐Shwartz, Shai Ben-David • Cambridge University Press eBooks
(2014)
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book prov...
OPENALEX
DOI: https://doi.org/10.1017/cbo9781107298019
David Barber • Cambridge University Press eBooks
(2012)
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...
OPENALEX
DOI: https://doi.org/10.1017/cbo9780511804779
Juan Carlos Ramírez-Vázquez, Guadalupe Esmeralda Rivera-García, Marco Antonio Gómez-Guzmán, Marco Antonio Díaz-Martínez et al. • Technologies
(2026)
A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/technologies14030189
Kevin P. Murphy (2012)
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict fu...
OPENALEX
Stephen Marsland • Chapman & Hall/CRC eBooks
(2014)
A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing wo...
OPENALEX
DOI: https://doi.org/10.1201/b17476
S. Sra, S. Nowozin, Stephen J. Wright • The MIT Press eBooks
(2011)
An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments ...
OPENALEX
DOI: https://doi.org/10.7551/mitpress/8996.001.0001
• Series in machine perception and artificial intelligence
(2019)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict ...
OPENALEX
DOI: https://doi.org/10.1142/9789811201967_0001
Michael Gofman, Zhao Jin • The Journal of Finance
(2023)
ABSTRACT We document an unprecedented brain drain of Artificial Intelligence (AI) professors from universities from 2004 to 2018. We find that students from the affected universities establish fewer AI startups and raise less funding. The b...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1111/jofi.13302
Zhongzhi Shi • WORLD SCIENTIFIC eBooks
(2011)
Artificial intelligence is a branch of computer science and a discipline in the study of machine intelligence, that is, developing intelligent machines or intelligent systems imitating, extending and augmenting human intelligence through ar...
OPENALEX
DOI: https://doi.org/10.1142/7547
Xue Han, Jing Cao, Zi Wang, Heng Luo • Behavioral Sciences
(2026)
This study examines how agent type (customized vs. general-purpose) and feedback style (Socratic vs. directive) are associated with learners’ engagement with artificial intelligence (AI)-generated feedback in self-directed learning (SDL), w...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bs16071069
Cristina Ramírez-Aroca, Arash Javadinejad • Education Sciences
(2026)
This study examines how Artificial Intelligence (AI) can enhance Content and Language Integrated Learning (CLIL) through embodied, multimodal instruction in secondary Physical Education (PE). Drawing on Fernández Fontecha’s Content and Lang...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/educsci16010062
Mireilla Bikanga Ada • Education Sciences
(2024)
This study explores how computing science students (n = 335) use ChatGPT, their trust in its information, their navigation of plagiarism issues, and their confidence in addressing plagiarism and academic integrity. A mixed-methods approach ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/educsci14101106
Philippa Boyd, Debs Harding • Buildings & Cities
(2025)
The uptake of generative artificial intelligence (GenAI) tools has implications for doctoral research and academic publication practices within both construction management and the wider academic context. Unless these implications are under...
DOAJ
Open Access (DOAJ)
DOI: 10.5334/bc.560
Eleni Fotopoulou, Anastasios Zafeiropoulos, Eleftheria Arkadopoulou, Christina-Maria Androna et al. • IEEE Access
(2026)
The positive impact of Social and Emotional Learning (SEL) activities in schools is widely recognized in various sectors, including mental health, social relationships, and academic performance of students. This impact can be efficiently re...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2026.3671870
Richard E. Neapolitan, Xia Jiang • Chapman & Hall/CRC eBooks
(2018)
The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machi...
OPENALEX
DOI: https://doi.org/10.1201/b22400
Renjing Zhang • Frontiers in Psychology
(2026)
BackgroundAs generative artificial intelligence (GenAI) rapidly permeates Chinese higher education, university students’ AI use behaviors have come to be characterized by “high frequency, wide penetration, and rapid iteration.” Yet, a syste...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fpsyg.2026.1914910