• various links to prune & absorb > https://pinboard.in/search/u:zzkt?query=machine-learning

• crm114 descriminator
• “Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering” » http://www.cs.cmu.edu/~mccallum/bow/

• A 'Brief' History of Neural Nets and Deep Learning. http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning/, http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning-part-2/, http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning-part-3/ and http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning-part-4/
• “Data Mining: Practical Machine Learning Tools and Techniques (Second Edition)” » http://www.cs.waikato.ac.nz/~ml/weka/book.html

• “Adoption of Machine Learning Techniques in #Ecology and Earth Science. Thessen [2016]” » https://t.co/D1hOba8AY7
• “Machine Learning without Tears: A primer for Ecologists. Olden et al [2008]” » https://t.co/N1l1JKYqqh
• "What do Buddist Monks Think about the Trolley Problem"
• "How The Random Forest Algorithm Works In Machine Learning"
• "Random Forest: Many Is Better Than One"

-see: http://machinewilderness.net