{"id":1144,"date":"2017-06-01T11:06:35","date_gmt":"2017-06-01T11:06:35","guid":{"rendered":"http:\/\/physics-complex-systems.fr\/?p=1144"},"modified":"2017-06-30T12:20:49","modified_gmt":"2017-06-30T12:20:49","slug":"inference-learning-big-data","status":"publish","type":"post","link":"https:\/\/physics-complex-systems.fr\/en\/inference-learning-big-data.html","title":{"rendered":"Inference, learning &#038; big data"},"content":{"rendered":"<p>[vc_row][vc_column css=&#8221;.vc_custom_1496399944725{margin-top: -40px !important;margin-bottom: -20px !important;}&#8221;][vc_separator][\/vc_column][\/vc_row][vc_row equal_height=&#8221;yes&#8221; content_placement=&#8221;top&#8221;][vc_column width=&#8221;1\/2&#8243;][vc_column_text]<\/p>\n<div style=\"text-align: justify; text-justify: inter-word; color: #363131;\">This course provides an introduction to the theory and the practice of inference and learning from data. I discuss the different kinds of learning from data: supervised, unsupervised and reinforcement learning. As a simple example of supervised learning I discuss the &#8220;perceptrons&#8221; and &#8220;support vector machines&#8221;. I also discuss in a lesser detail multilayer neural networks and &#8220;deep learning&#8221;. The problem of data clustering is addressed in detail and used to illustrate unsupervised learning. I discuss applications from computer revised learning. I discuss applications from computer science (hand writing recognition, matrix completion), biology (inverse Ising models for protein folding), and associative memory (Hopfield model). The course includes 3 tutorials to implement the discussed algorithms.<\/div>\n<div><\/div>\n<div><strong>Bibliography<\/strong><\/div>\n<ul>\n<li class=\"lastItem\"><em>Information Theory, Inference, and Learning Algorithms<\/em>, D.J.C. MacKay, Cambridge University Press.<\/li>\n<li><em>The Elements of Statistical Learning: Data Mining, Inference and Prediction<\/em>,T. Hastie, R. Tibshirani and J. Friedman, Springer.<\/li>\n<li><em>Statistical Mechanics of Learning<\/em>, A. Engel and C. Van den Broeck, Cornell University Press.<\/li>\n<li><em>Data Classification Algorithms and Applications<\/em>, C. C. Aggarwal, Chapman &amp; Hall\/CRC Data Mining and Knowledge Discovery Series.<\/li>\n<\/ul>\n<p>[\/vc_column_text][vc_column_text]<img loading=\"lazy\" decoding=\"async\" class=\"alignleft size-full wp-image-1145\" src=\"http:\/\/physics-complex-systems.fr\/wp-content\/uploads\/2017\/06\/Fanz.jpg\" alt=\"\" width=\"90\" height=\"120\" \/>Silvio Franz<br \/>\n(Universit\u00e9 Paris-Sud\/Paris-Saclay)[\/vc_column_text][\/vc_column][vc_column width=&#8221;1\/2&#8243; css=&#8221;.vc_custom_1496308532682{background-color: #fcfcfc !important;}&#8221;][vc_single_image image=&#8221;1146&#8243; img_size=&#8221;full&#8221; alignment=&#8221;center&#8221;][\/vc_column][\/vc_row][vc_row css=&#8221;.vc_custom_1496826788251{margin-top: 20px !important;}&#8221;][vc_column][vc_column_text]<\/p>\n<div class=\"displaytags\" style=\"color: #363131;\">Keywords : <span class=\"etiquette-key\">Data clustering<\/span> <span class=\"etiquette-key\">Deep learning<\/span> <span class=\"etiquette-key\">Inference<\/span> <span class=\"etiquette-key\">Neural Networks<\/span> <span class=\"etiquette-key\">Perceptrons<\/span> <span class=\"etiquette-key\">Supervised Learning<\/span><\/div>\n<p>[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column css=&#8221;.vc_custom_1496399944725{margin-top: -40px !important;margin-bottom: -20px !important;}&#8221;][vc_separator][\/vc_column][\/vc_row][vc_row equal_height=&#8221;yes&#8221; content_placement=&#8221;top&#8221;][vc_column width=&#8221;1\/2&#8243;][vc_column_text] This course provides an introduction to the theory and the practice of inference and learning from&#8230;<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[83,10],"tags":[107,106,103,105,108,104],"translation":{"provider":"WPGlobus","version":"2.12.2","language":"en","enabled_languages":["fr","en"],"languages":{"fr":{"title":true,"content":true,"excerpt":false},"en":{"title":false,"content":false,"excerpt":false}}},"_links":{"self":[{"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/posts\/1144"}],"collection":[{"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/comments?post=1144"}],"version-history":[{"count":15,"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/posts\/1144\/revisions"}],"predecessor-version":[{"id":1976,"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/posts\/1144\/revisions\/1976"}],"wp:attachment":[{"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/media?parent=1144"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/categories?post=1144"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/physics-complex-systems.fr\/en\/wp-json\/wp\/v2\/tags?post=1144"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}