Results 221 to 230 of about 186,399 (262)

Teaching Quantum Machine Learning in Computer Science

2023 IEEE 15th International Symposium on Autonomous Decentralized System (ISADS), 2023
Yinong Chen
exaly   +2 more sources

Design of Quantum Machine Learning Course for a Computer Science Program

2023 IEEE International Conference on Quantum Computing and Engineering (QCE), 2023
Sathish Kumar, Ahmad AlOmari
exaly   +2 more sources

Teaching Machine Learning to Computer Science Preservice Teachers

Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, 2021
Machine learning is a fast-growing field with various applications in artificial intelligence and data science. Recently, a new machine learning program have been integrated into the Israeli high school computer science curriculum and thus we added a new machine learning module to the Methods of Teaching Computer Science (MTCS) course, which is part of
Koby Mike, Rinat B. Rosenberg-Kima
openaire   +1 more source

A Bridge to Machine Learning for Zero Computer Science Community: A Machine Learning Path with Linear Regression

International Conference on Intelligent and Innovative Computing Applications, 2022
Based on LinkedIn poll results, professionals from non-computer science backgrounds have developed an interest in data science and most intend to enter the field through Machine Learning, but do not know where to start (Webb et al., 2021) The aim of this study is to introduce an ideal systematic approach and workflow to get started with Machine ...
Malusi Sibiya, Elisha Didam Markus
openaire   +1 more source

A short review on the application of computational intelligence and machine learning in the bioenvironmental sciences

The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, 2012
This paper aims to provide a short review on the application of computational intelligence (CI) and machine learning (ML) in the bioenvironmental sciences. To clearly illustrate the current status, we limit our focus to some key approaches, namely fuzzy systems (FSs), artificial neural networks (ANNs) and genetic algorithms (GAs) as well as some ML ...
Shinji Fukuda, Bernard De Baets
openaire   +1 more source

Machine Learning in Building a Collection of Computer Science Course Syllabi

2012
Syllabi are rich educational resources. However, finding Computer Science syllabi on a generic search engine does not work well. Towards our goal of building a syllabus collection we have trained various Decision Tree, Naive-Bayes, Support Vector Machine and Feed-Forward Neural Network classifiers to recognize Computer Science syllabi from other web ...
Nakul Rathod, Lillian N. Cassel
openaire   +1 more source

Recent Advances in Numerical Methods, Machine Learning, and Computer Science

2021
The chapter presents a brief description of chapters that contribute to the recent advances in numerical methods in continuum mechanics, computational physics. Also, this chapter deals with machine learning and computer science. The fourth part of the book presents novel computational methods in continuum mechanics.
Margarita N. Favorskaya, Alena V. Favorskaya, Igor B. Petrov, Lakhmi C. Jain   +3 more
openaire   +1 more source

THE INTRODUCTION OF MACHINE LEARNING INTO COMPUTER SCIENCE CURRICULA

EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA
The article examines the relevance and necessity of integrating machine learning (ML) into computer science curricula. Modern trends and approaches to teaching ML in educational institutions of different levels are analyzed, examples of successful implementation are given, and problems and prospects of this process are considered.
Ekaterina V. Abzaldinova, Ildar M. Safarov   +1 more
openaire   +1 more source

A Machine Learning Approach to Performance and Dropout prediction in Computer Science: Bangladesh Perspective

2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2020
This is an era of computers and technology. Nowadays Computer Science (C.S.) and other technology-related subjects are a hot cake for the students. Due to a good job market for these subjects, students are taking computer science and other related topics without thinking about their capability and without knowing the curriculum of these subjects.
Sheikh Arif Ahmed, Md. Aref Billah, Shahidul Islam Khan   +2 more
openaire   +1 more source

Machine Learning for Data Science: Mathematical or Computational

2015
Machine learning usually requires getting a training and testing set of samples. The training set is used to obtain the model, and then, the testing set is used to verify the model. In general, a machine learning method requires an iterated process for reaching a goal. Machine learning is one of the research areas in artificial intelligence.
openaire   +1 more source