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Machine Learning

1st Edition 2021, 2021

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Self-study in learning foreign language: 190 To conclude, research can be fun, interesting and fascinating. A feeling of accomplishment, satisfaction, and pride can be the result of contributing to the ―greater cause‖ of our ―way of knowing.‖ Research is a complex, exacting, and complex process that yields the ultimate reward of truth or at least a path leading to it [Bailey, D. M.: 1997]. Using innovative ways of doing research is one to achieve a great goal. REFERENCES: 1. Çaparlar CÖ, Dönmez A. What is Scientific Research and How Ca

Ренессанс в парадигме новаций образования и технологий в XXI веке, 2022-05 (1), p.191-193

2022

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Mobile as Mainstream - Towards Future Challenges in Mobile Learning: 13th World Conference on Mobile and Contextual Learning, mLearn 2014, Istanbul, Turkey, November 3-5, 2014. Proceedings

1, 2014

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Imitation Learning: A Survey of Learning Methods

ACM computing surveys, 2018-03, Vol.50 (2), p.1-35

2018

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Chatbots for language learning—Are they really useful? A systematic review of chatbot‐supported language learning

Journal of computer assisted learning, 2022-02, Vol.38 (1), p.237-257

2022

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An Introduction to Statistical Learning: with Applications in R

1, 2013

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Benefits and drawbacks of distance learning in teaching language: Global dunyoda ilm-fan va ta‘limdagi innovatsion rivojlanishning zamonaviy trendlari 15 dekabr, 2022 yil. 372 Abstract: This article illustrates current trends in online teaching a language. However, the article discusses advantages and disadvantages of distance teaching. For the time be-ing new innovative technologies, allow an opportunity to learn and teach target language without any awkwardness. Keywords: innovations, electronic technologies, global pandemic, distance learning, ac- cessible

Современные тенденции инновационного развития науки и образования в глобальном мире, 2023-03, Vol.1 (3), p.372-375

Nizomova, Iroda

2023

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Learning SO

International journal of computer vision, 2020-03, Vol.128 (3), p.588

2020

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Visible Learning: The Sequel : A Synthesis of Over 2,100 Meta-Analyses Relating to Achievement

Hattie, John

New edition, 2023

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Reinforcement Learning: Aktuelle Ansätze Verstehen - Mit Beispielen in Java und Greenfoot

Lorenz, Uwe

2. Aufl. 2024, 2024

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Sprachförderung in DaZ

2024

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Deep learning

Nature (London), 2015-05, Vol.521 (7553), p.436-444

2015

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Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning

Jo, Taeho

1st Edition 2021, 2021

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The Black Box of Governmental Learning: The Learning Spiral - A Concept to Organize Learning in Governments

1, 2010

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Deep learning

Nature methods, 2016-01, Vol.13 (1), p.35-35

Rusk, Nicole

2016

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Learning: Interdisciplinarity and Learning

1, 2021

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Machine learning and deep learning

Electronic markets, 2021-09, Vol.31 (3), p.685-695

2021

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Metric Learning

Synthesis lectures on artificial intelligence and machine learning, 2015, Vol.9 (1), p.1-151

2015

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Pedagogy and innovative teaching methods in the xxi century: 210 same time it is a reflection of the manifestation of the will or internal acceptance of the value of the task [ Ryan R.M., Deci E.L. ] Motives and motivation are the driving force behind the learning process. It is motivation that is the main means that will make it possible to increase the level of students' interest in the educational process. Therefore, the education system as a whole and teachers, as the most important subjects of this system, should always pay great attention to the pri

Ренессанс в парадигме новаций образования и технологий в XXI веке, 2022-05 (1), p.211-213

2022

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Machine Learning in Medical Imaging: 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings

1st ed. 2021., 2021

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Dual Learning

Qin, Tao

1st Edition 2020, 2020

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Federated Learning

Synthesis lectures on artificial intelligence and machine learning, 2020, Vol.13 (3), p.1-207

2020

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Hyperparameter Optimization in Machine Learning: Make Your Machine Learning and Deep Learning Models More Efficient

Agrawal, Tanay

1st Edition, 2020

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Learning Diversity

Peterlini, Hans Karl

1st Edition 2023, 2023

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Increased fear learning, spatial learning as well as neophobia in Rgs2−/− mice

Genes, brain and behavior, 2018-04, Vol.17 (4), p.e12420-n/a

2018

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Machine Learning

Mobile as Mainstream - Towards Future Challenges in Mobile Learning: 13th World Conference on Mobile and Contextual Learning, mLearn 2014, Istanbul, Turkey, November 3-5, 2014. Proceedings

Imitation Learning: A Survey of Learning Methods

Chatbots for language learning—Are they really useful? A systematic review of chatbot‐supported language learning

An Introduction to Statistical Learning: with Applications in R

Learning SO

Visible Learning: The Sequel : A Synthesis of Over 2,100 Meta-Analyses Relating to Achievement

Reinforcement Learning: Aktuelle Ansätze Verstehen - Mit Beispielen in Java und Greenfoot

Sprachförderung in DaZ

Deep learning

Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning

The Black Box of Governmental Learning: The Learning Spiral - A Concept to Organize Learning in Governments

Deep learning

Learning: Interdisciplinarity and Learning

Machine learning and deep learning

Metric Learning

Machine Learning in Medical Imaging: 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings

Dual Learning

Federated Learning

Hyperparameter Optimization in Machine Learning: Make Your Machine Learning and Deep Learning Models More Efficient

Learning Diversity

Increased fear learning, spatial learning as well as neophobia in Rgs2−/− mice

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