![\"osgeo\"](\"http:\/\/blog.light42.com\/wordpress\/wp-content\/uploads\/2019\/10\/osgeolive-logo-lg.png\"){kind=logo}
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On the OSGeo Japan -discuss mailing list regarding FOSS4G<\/strong> 2019 KOBE.KANSAI<\/strong> :<\/p>\n \u4eca\u5e74\u306f\u3001Geo-AI<\/strong>\u306e\u30c6\u30fc\u30de\u306b\u30de\u30c3\u30c1\u3057\u305f\u3001\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u306e\u52c9\u5f37\u304c\u521d\u6b69\u304b\u3089\u4f53\u9a13\u3067\u304d\u308b\u30b3\u30fc\u30b9\u304c\uff12\u3064\u3042\u308a\u307e\u3059\uff01<\/p>\n \u00a0 translation: this year, there are two courses that match the theme of Geo-AI<\/strong>, where you can experience deep learning from the beginning!<\/em><\/p>\n An OSGeo Japan wiki page<\/a> says:\u00a0 \u00a0 \u4eca\u5e74\u306e\u30c6\u30fc\u30de\u306f\u300cGeo-AI\u300d\u3067\u3059\u3002 Geo-AI<\/strong> a closer look – “geo” is easy, what about AI?<\/p>\n a working definition of AI*:<\/em> Data Science overlaps Artificial Intelligence, Machine Learning exists in that overlap.<\/p><\/div>\n When people speak about Machine Learning<\/strong> these days, they are often speaking of Deep Learning<\/strong>, a subset of Artificial Neural Networks NN<\/strong>.. networks consisting of connected, simple processors called “neurons” wikipedia<\/em> -LINK-nn<\/a> -LINK-dl<\/a> This blog post -LINK-<\/a> describes NN training methods, including “weakly supervised<\/em>” and “transfer learning<\/em>.”<\/p>\n Since 2009, supervised deep NN<\/strong>‘s have won many awards in international pattern recognition competitions, achieving better-than-human results in some limited domains.<\/em> — Schmidhuber 2015 Survey of Deep Learning<\/strong><\/p>\n Deep Learning is especially effective on data sets like images and sound, and typically improve with the amount of training data available. Deep Learning<\/strong> is not new, but what is new are the volumes of available labelled training data, and the capacity to compute on them. Many Deep Learning programming libraries are in Python<\/strong>, and many libraries run natively on a GPU<\/strong>. -LINK-sklearn<\/a> -LINK-pyTorch<\/a><\/p>\n Data Science<\/strong> uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.<\/em> wikipedia -LINK-ds<\/a><\/p>\n
\n\u00a0 \u00a0 translation: this year’s theme is \u201cGeo-AI\u201d.<\/em><\/p>\n
\n A<\/span>rtificial I<\/span>ntelligence<\/strong> is the theory and development of computer systems able to perform tasks which previously required human intelligence.\u00a0 AI<\/strong> is a broad field, of which Machine Learning ML<\/strong> is a sub-category.<\/p>\n![\"ds_ml_ai\"](\"http:\/\/blog.light42.com\/wordpress\/wp-content\/uploads\/2019\/10\/AI_ml_DLf.png\")