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machine_learning [2017-07-10 19:13] theunkarelsemachine_learning [2017-08-07 21:39] (current) nik
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 +===Machine Learning===
 +
 +  * various links to prune & absorb > https://pinboard.in/search/u:zzkt?query=machine-learning
 +
 +
 +===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/
  
-===reading=== 
-  * "Data Mining: Practical Machine Learning Tools and Techniques (Second Edition)" >> http://www.cs.waikato.ac.nz/~ml/weka/book.html 
  
-===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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