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machine_learning [2017-07-10 19:13] – theunkarelse | machine_learning [2017-08-07 21:39] (current) – nik |
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| ===Machine Learning=== |
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| * various links to prune & absorb > https://pinboard.in/search/u:zzkt?query=machine-learning |
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| ===reading=== |
| * A 'Brief' History of Neural Nets and Deep Learning. [[http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning/|part 1]], [[http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning-part-2/|part 2]], [[http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning-part-3/|part 3]] and [[http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning-part-4/|part 4]] |
| * "Data Mining: Practical Machine Learning Tools and Techniques (Second Edition)" >> http://www.cs.waikato.ac.nz/~ml/weka/book.html |
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* "Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering" >> http://www.cs.cmu.edu/~mccallum/bow/ | * "Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering" >> http://www.cs.cmu.edu/~mccallum/bow/ |
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===reading=== | |
* "Data Mining: Practical Machine Learning Tools and Techniques (Second Edition)" >> http://www.cs.waikato.ac.nz/~ml/weka/book.html | |
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===in ecology=== | ===misclassifier systems=== |
* "Adoption of Machine Learning Techniques in #Ecology and Earth Science. Thessen [2016]" >> https://t.co/D1hOba8AY7 | * see [[Robust Physical Perturbations]] |
* "Machine Learning without Tears: A primer for Ecologists. Olden et al [2008]" >> https://t.co/N1l1JKYqqh | * adversarial methods |
* [[https://www.theatlantic.com/technology/archive/2017/06/how-do-buddhist-monks-think-about-the-trolley-problem/532092/|"What do Buddist Monks Think about the Trolley Problem"]] | |
* [[https://topdata.news/how-the-random-forest-algorithm-works-in-machinelearning/|"How The Random Forest Algorithm Works In Machine Learning"]] | |
* [[https://quantdare.com/random-forest-many-is-better-than-one/|"Random Forest: Many Is Better Than One"]] | |
-see: http://machinewilderness.net | see also: [[environmental machine learning]] |
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