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1. link.springer.com › chapter › 10Machine Learning Algorithms - Springer

   link.springer.com › chapter › 10

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   3 dni temu · Machine learning (ML) a branch of artificial intelligence (AI) that enables computers to self-learn from data and improve over time, without being explicitly programmed. Machine learning algorithms are able to detect patterns in data and learn from them, in order to make their own predictions. In short, machine learning algorithms and models ...

2. www.analyticsvidhya.com › blog › 2015Machine Learning Basic Concepts, ML Fundamentals PDF - Analytics...

   www.analyticsvidhya.com › blog › 2015

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   4 lip 2024 · Read our article on Basic ML concepts (Machine learnings) and techniques: supervised, unsupervised, reinforcement learning, and real-world applications.

3. koalaverse.github.io › homlr-2edHands-On Machine Learning with R, 2ed - GitHub Pages

   koalaverse.github.io › homlr-2ed

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   6 dni temu · This book provides hands-on modules for many of the most common machine learning methods to include: Generalized low rank models. Clustering algorithms. Autoencoders. Regularized models. Random forests. Gradient boosting machines. Deep neural networks. Stacking / super learners.

4. www.geeksforgeeks.org › machine-learningMachine Learning Tutorial - GeeksforGeeks

   www.geeksforgeeks.org › machine-learning

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   20 cze 2024 · This machine learning tutorial helps you gain a solid introduction to the fundamentals of machine learning and explore a wide range of techniques, including supervised, unsupervised, and reinforcement learning.

5. link.springer.com › book › 10Learning Analytics Methods and Tutorials - Springer

   link.springer.com › book › 10

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   24 cze 2024 · The book covers all important quantitative topics in education at large as well as the latest in learning analytics and education data mining. The book also goes deeper into advanced methods that are at the forefront of novel methodological innovations.

6. arxiv.org › list › csMachine Learning - arXiv.org

   arxiv.org › list › cs

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   8 lip 2024 · Subjects:Machine Learning (cs.LG); Neural and Evolutionary Computing (cs.NE); Dynamical Systems (math.DS); Adaptation and Self-Organizing Systems (nlin.AO)

7. mlstory.orgPatterns, Predictions, and Actions

   mlstory.org

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   18 cze 2024 · A story about machine learning. Moritz Hardt and Benjamin Recht. Image copyright: Princeton University Press. Hardcover. Princeton University Press. Errata. Full preprint as PDF. Problem sets (pdf) Table of contents. Preface. Acknowledgments. Introduction ( PDF) Fundamentals of prediction ( PDF) Supervised learning ( PDF)