{"id":767,"date":"2018-05-23T14:13:24","date_gmt":"2018-05-23T14:13:24","guid":{"rendered":"http:\/\/eic.cefet-rj.br\/~ebezerra\/?page_id=767"},"modified":"2018-08-30T11:56:13","modified_gmt":"2018-08-30T11:56:13","slug":"ml2018","status":"publish","type":"page","link":"https:\/\/eic.cefet-rj.br\/~ebezerra\/ml2018\/","title":{"rendered":"Aprendizado de M\u00e1quina (2018)"},"content":{"rendered":"<p>&nbsp;<\/p>\n<figure id=\"attachment_144\" aria-describedby=\"caption-attachment-144\" style=\"width: 453px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/www.kdnuggets.com\/images\/cartoon-machine-learning-class.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\" wp-image-144\" src=\"https:\/\/www.kdnuggets.com\/images\/cartoon-machine-learning-class.jpg\" alt=\"\" width=\"453\" height=\"337\" \/><\/a><figcaption id=\"caption-attachment-144\" class=\"wp-caption-text\">&#8220;Teacher: Robbie, stop misbehaving or I will send you back to data cleaning.&#8221;<\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<hr \/>\n<h3>Cursos<\/h3>\n<ul>\n<li>Mestrado em Ci\u00eancia da Computa\u00e7\u00e3o<\/li>\n<\/ul>\n<h3>Local\/hor\u00e1rio<\/h3>\n<ul>\n<li>Bloco E, 5o andar, sala E-522<\/li>\n<li>Dia\/hor\u00e1rio: 5as-feiras, das 13:25h \u00e0s 17:00h<\/li>\n<\/ul>\n<hr \/>\n<h3>Apresenta\u00e7\u00e3o<\/h3>\n<p>Aprendizado de M\u00e1quina (<em>Machine Learning<\/em>) \u00e9 um campo de estudo da Intelig\u00eancia Artificial cujo objeto de estudo s\u00e3o sistemas que podem aprender a realizar alguma tarefa por meio de experi\u00eancias. Neste curso, o objetivo \u00e9 apresentar uma introdu\u00e7\u00e3o aos conceitos, modelos, m\u00e9todos, t\u00e9cnicas e aplica\u00e7\u00f5es do Aprendizado de M\u00e1quina. S\u00e3o tamb\u00e9m apresentados alguns algoritmos pertencentes a diferentes fam\u00edlias de m\u00e9todos em AM (simbolistas, conexionistas, probabil\u00edsticos, baseados em proximidade).<\/p>\n<hr \/>\n<h3>Livros<\/h3>\n<ul>\n<li>Christopher Bishop, <a href=\"https:\/\/www.springer.com\/br\/book\/9780387310732\">Pattern Recognition and Machine Learning<\/a>, Springer, 2006.<\/li>\n<li>Ethen Alpaydin, <a href=\"https:\/\/mitpress.mit.edu\/books\/introduction-machine-learning\">Introduction to Machine Learning<\/a>, MIT Press, 2010.<\/li>\n<li>Ian Goodfellow et al, <a href=\"http:\/\/www.deeplearningbook.org\/\">Deep Learning<\/a>, MIT Press, 2016.<\/li>\n<li>Sebastian Raschka, <a href=\"https:\/\/www.amazon.com.br\/Python-Machine-Learning-scikit-learn-TensorFlow-ebook\/dp\/B0742K7HYF\/ref=dp_ob_image_def\">Python Machine Learning<\/a>, 2nd ed, Packt Publishing, 2015.<\/li>\n<li>Tom Mitchell, <a href=\"http:\/\/www.cs.cmu.edu\/afs\/cs.cmu.edu\/user\/mitchell\/ftp\/mlbook.html\">Machine Learning<\/a>, McGraw-Hill, 1997.<\/li>\n<\/ul>\n<hr size=\"4\" width=\"100%\" \/>\n<h3>Plano de curso<\/h3>\n<p>Veja tamb\u00e9m o <a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/DIPPG_calendario_2018.pdf\">calend\u00e1rio acad\u00eamico das p\u00f3s-gradua\u00e7\u00f5es<\/a> do CEFET\/RJ. Veja ainda a <a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/am-complementar\/\">p\u00e1gina<\/a> com material relevante organizado por aula.<\/p>\n<table style=\"border: 1px solid #cccccc;\">\n<tbody>\n<tr>\n<td style=\"border: 1px solid #cccccc;\"><b>Aula<\/b><\/td>\n<td style=\"border: 1px solid #cccccc;\"><b>Data<\/b><\/td>\n<td style=\"border: 1px solid #cccccc;\"><b>T\u00f3pico<\/b><\/td>\n<td style=\"border: 1px solid #cccccc;\"><b>Leitura<\/b><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">1<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">24\/mai<\/td>\n<td style=\"border: 1px solid #cccccc;\">Log\u00edstica do curso, plano de aulas (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2017\/07\/AM-00-Apresenta\u00e7\u00e3o-da-Disciplina.pptx\">AM_00<\/a>).<br \/>\nDefini\u00e7\u00e3o, motiva\u00e7\u00e3o,\u00a0vis\u00e3o geral e exemplos de aplica\u00e7\u00f5es (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2017\/07\/AM-01-Vis\u00e3o-geral-do-Aprendizado-de-m\u00e1quina.pptx\">AM_01<\/a>).<br \/>\nRegress\u00e3o linear com uma vari\u00e1vel (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2017\/07\/AM-02-Regress\u00e3o-Linear-com-Uma-Vari\u00e1vel.pptx\">AM_02<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc;\">Mitchell, Cap. 1; <a href=\"http:\/\/www.cs.cmu.edu\/%7Etom\/mlbook\/keyIdeas.pdf\">paper<\/a>;\u00a0<a href=\"http:\/\/homes.cs.washington.edu\/~pedrod\/papers\/cacm12.pdf\">paper<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a02<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a007\/jun<\/td>\n<td style=\"border: 1px solid #cccccc;\">Regress\u00e3o linear com v\u00e1rias vari\u00e1veis (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-03-Regress\u00e3o-Linear-Multivariada.pptx\">AM_03<\/a>)<br \/>\nRegress\u00e3o log\u00edstica (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-04-Regress\u00e3o-Log\u00edstica.pptx\">AM_04<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc;\"><a href=\"http:\/\/adit.io\/posts\/2016-03-13-Logistic-Regression.html\">regress\u00e3o log\u00edstica<\/a>; <a href=\"http:\/\/adit.io\/posts\/2016-02-20-Linear-Regression-in-Pictures.html\">regress\u00e3o linear<\/a>; <a href=\"http:\/\/cs229.stanford.edu\/notes\/cs229-notes1.pdf\">cs229-notes1<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a03<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a014\/jun<\/td>\n<td style=\"border: 1px solid #cccccc;\">Regulariza\u00e7\u00e3o, valida\u00e7\u00e3o cruzada (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-05-Regulariza\u00e7\u00e3o.pptx\">AM_05<\/a>)<br \/>\nProjeto e an\u00e1lise de experimentos em AM (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-06-Refinamento-de-Algoritmos-de-AM.pptx\">AM_06<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc;\"><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a04<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a021\/jun<\/td>\n<td style=\"border: 1px solid #cccccc;\">Agrupamento (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-07-Agrupamento-.pptx\">AM_07<\/a>); Redu\u00e7\u00e3o de Dimensionalidade (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-08-Redu\u00e7\u00e3o-de-Dimensionalidade.pptx\">AM_08<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc;\">Alpaydin, Caps. 6 e 7; <a href=\"https:\/\/cefetrjbr-my.sharepoint.com\/:u:\/r\/personal\/02848884789_cefet-rj_br\/Documents\/am-aulas2018\/AM-PCA.ipynb?csf=1&amp;e=pMaDSM\">PCA.ipynb<\/a>; <a href=\"https:\/\/www.youtube.com\/watch?v=EokL7E6o1AE\">SVD<\/a>; <a href=\"https:\/\/www.youtube.com\/watch?v=kjBOesZCoqc&amp;list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab\">linear algebra<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">5<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a028\/jun<\/td>\n<td style=\"border: 1px solid #cccccc;\">Detec\u00e7\u00e3o de Anomalias (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-09-Detec\u00e7\u00e3o-de-Anomalias.pptx\">AM_09<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc;\"><a href=\"http:\/\/cucis.ece.northwestern.edu\/projects\/DMS\/publications\/AnomalyDetection.pdf\">paper<\/a>; <a href=\"https:\/\/cefetrjbr-my.sharepoint.com\/:u:\/r\/personal\/02848884789_cefet-rj_br\/Documents\/am-aulas2018\/AM-gaussians.ipynb?csf=1&amp;e=JM7dXW\">gaussians.ipynb<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a06<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a005\/jul<\/td>\n<td style=\"border: 1px solid #cccccc;\">Sistemas de Recomenda\u00e7\u00e3o (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-10-Sistemas-de-Recomenda\u00e7\u00e3o.pptx\">AM_10<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc;\"><a href=\"https:\/\/courses.cs.washington.edu\/courses\/csep546\/17au\/psetwww\/2\/algsweb.pdf\">paper<\/a>;<\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a07<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">26\/jul<\/td>\n<td style=\"border: 1px solid #cccccc;\">\u00c1rvores de Decis\u00e3o (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-11-A\u0301rvores-de-Decisa\u0303o.pptx\">AM_11<\/a>); Aprendizado de Comit\u00eas (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-12-Aprendizado-de-Comit\u00eas.pptx\">AM_12<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc;\"><a href=\"http:\/\/robotics.stanford.edu\/~ronnyk\/vote.pdf\">paper<\/a>; <a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-ensembles.pdf\">ensembles.ipynb<\/a>; <a href=\"https:\/\/gist.github.com\/tomokishii\/8290b06cd908a9fb694b217e8e09a46b\">MLInP-Chap7.ipynb<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a08<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">02\/ago<\/td>\n<td style=\"border: 1px solid #cccccc;\">Redes Neurais &#8211; Representa\u00e7\u00e3o (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-13-Redes-Neurais-Representa\u00e7\u00e3o.pptx\">AM_13<\/a>) &amp; Aprendizado (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-14-Redes-Neurais-Aprendizado.pptx\">AM_14<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: left;\"><a href=\"https:\/\/towardsdatascience.com\/the-mostly-complete-chart-of-neural-networks-explained-3fb6f2367464\">link<\/a>; <a href=\"https:\/\/playground.tensorflow.org\/#activation=tanh&amp;batchSize=10&amp;dataset=circle&amp;regDataset=reg-plane&amp;learningRate=0.03&amp;regularizationRate=0&amp;noise=0&amp;networkShape=4,2&amp;seed=0.25436&amp;showTestData=false&amp;discretize=false&amp;percTrainData=50&amp;x=true&amp;y=true&amp;xTimesY=false&amp;xSquared=false&amp;ySquared=false&amp;cosX=false&amp;sinX=false&amp;cosY=false&amp;sinY=false&amp;collectStats=false&amp;problem=classification&amp;initZero=false&amp;hideText=false\">link<\/a>; <a href=\"http:\/\/colah.github.io\/posts\/2015-08-Backprop\/\">link<\/a>; <a href=\"http:\/\/www.iro.umontreal.ca\/~pift6266\/A06\/refs\/backprop_old.pdf\">paper<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a09<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">09\/ago<\/td>\n<td style=\"border: 1px solid #cccccc;\">Redes Neurais &#8211; Introdu\u00e7\u00e3o ao TensorFlow (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/Tensorflow.pptx\">AM_15<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: left;\">\u00a0<a href=\"https:\/\/github.com\/ramonsilvanet\/getting-started-tf\">link<\/a>; <a href=\"https:\/\/playground.tensorflow.org\/#activation=tanh&amp;batchSize=10&amp;dataset=circle&amp;regDataset=reg-plane&amp;learningRate=0.03&amp;regularizationRate=0&amp;noise=0&amp;networkShape=4,2&amp;seed=0.66317&amp;showTestData=false&amp;discretize=false&amp;percTrainData=50&amp;x=true&amp;y=true&amp;xTimesY=false&amp;xSquared=false&amp;ySquared=false&amp;cosX=false&amp;sinX=false&amp;cosY=false&amp;sinY=false&amp;collectStats=false&amp;problem=classification&amp;initZero=false&amp;hideText=false\">link<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a010<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">16\/ago<\/td>\n<td style=\"border: 1px solid #cccccc;\">Redes Neurais &#8211; Aprendizado &#8211; GD e variantes (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-16-Redes-Neurais-Aprendizado-GD-e-variantes.pptx\">AM_16<\/a>)<br \/>\nRedes neurais &#8211; Aprendizado &#8211; misc (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-17-Redes-Neurais-Aprendizado-misc.pptx\">AM_17<\/a>)<br \/>\nRedes neurais convolucionais (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-18-Redes-Convolucionais.pptx\">AM_18<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: left;\"><a href=\"https:\/\/cs.nyu.edu\/~fergus\/papers\/zeilerECCV2014.pdf\">Visualizing and Understanding CNNs<\/a><br \/>\n<a href=\"http:\/\/brohrer.github.io\/how_convolutional_neural_networks_work.html\">How do CNNs work<\/a><br \/>\n<a href=\"http:\/\/www.evolvingai.org\/fooling\">Deep neural networks are easily fooled<\/a><br \/>\n<a href=\"https:\/\/distill.pub\/2017\/feature-visualization\/\">Feature Visualization<\/a><br \/>\n<a href=\"https:\/\/blog.ycombinator.com\/how-adversarial-attacks-work\/\">How Adversarial Attacks Work<\/a><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/intuitively-understanding-convolutions-for-deep-learning-1f6f42faee1\">Intuitively Understanding Convolutions<\/a><\/td>\n<\/tr>\n<tr>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">\u00a011<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: center;\">23\/ago<\/td>\n<td style=\"border: 1px solid #cccccc;\">Redes autocodificadoras (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-19-Redes-Autocodificadoras.pptx\">AM_19<\/a>)<br \/>\nRedes recorrentes (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-20-Redes-Recorrentes.pptx\">AM_20<\/a>)<br \/>\nFechamento\/retrospectiva (<a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/AM-21-Considerac\u0327o\u0303es-Finais.pptx\">AM_21<\/a>)<\/td>\n<td style=\"border: 1px solid #cccccc; text-align: left;\"><a href=\"https:\/\/goo.gl\/forms\/fb4M1qUalW6bIU7v1\">Formul\u00e1rio de avalia\u00e7\u00e3o do curso<\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<hr size=\"4\" width=\"100%\" \/>\n<h3>Trabalhos pr\u00e1ticos<\/h3>\n<ul>\n<li>Trabalho 1 &#8211; <a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/am-trabalho01-2018.pdf\">enunciado<\/a> (dados no Moodle).\u00a0<span style=\"color: #ff0000;\">Entrega: <del>30\/jun<\/del> 02\/jul<\/span>.<\/li>\n<li>Trabalho 2 &#8211; <a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/am-trabalho02-2018.pdf\">enunciado <\/a>(dados no Moodle). <span style=\"color: #ff0000;\">Entrega: 22\/jul<\/span>.<\/li>\n<li>Trabalho 3 &#8211; <a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/am-2018-trabalho03.pdf\">enunciado<\/a> (dados no Moodle). <span style=\"color: #ff0000;\">Entrega: <del>12\/ago<\/del> 14\/ago<\/span>.<\/li>\n<li>Trabalho 4 &#8211; <a href=\"http:\/\/eic.cefet-rj.br\/~ebezerra\/wp-content\/uploads\/2018\/05\/am-2018-trabalho04.pdf\">enunciado<\/a> (dados no Moodle). <span style=\"color: #ff0000;\">Entrega: <del>30\/ago.<\/del> 07\/set<\/span>.<\/li>\n<\/ul>\n<hr size=\"4\" width=\"100%\" \/>\n<h3>Recursos externos<\/h3>\n<ul>\n<li>V\u00eddeo: <a href=\"https:\/\/www.youtube.com\/watch?v=iX5V1WpxxkY\">Recurrent Neural Networks, Image Captioning, LSTM<\/a>, Andrej Karpathy.<\/li>\n<li>Curso online: <a href=\"http:\/\/course.fast.ai\">Practical Deep Learning For Coders<\/a><\/li>\n<li>Curso online: <a href=\"https:\/\/www.coursera.org\/learn\/neural-networks-deep-learning\">Neural Networks and Deep Learning<\/a><\/li>\n<li>Curso online: <a href=\"https:\/\/www.codecademy.com\/learn\/learn-python\">(Codecademy) Learn Python<\/a><\/li>\n<li><a href=\"http:\/\/w4nderlu.st\/teaching\/word-embeddings\">Word Embeddings<\/a><\/li>\n<li><a href=\"https:\/\/www.youtube.com\/watch?v=ZSDrM-tuOiA\">Representation Learning for Reading Comprehension<\/a><\/li>\n<li><a href=\"https:\/\/www.oreilly.com\/learning\/generative-adversarial-networks-for-beginners\">Practical Generative Adversarial Networks for Beginners<\/a><\/li>\n<\/ul>\n<hr size=\"4\" width=\"100%\" \/>\n<h3>Livros<\/h3>\n<ul>\n<li>David Poole &amp; . Machine Learning: A Probabilistic Perspective. The MIT Press, Cambridge, MA, 1 edition edition, August 2012.<\/li>\n<li>Kevin P. Murphy. Machine Learning: A Probabilistic Perspective. The MIT Press, Cambridge, MA, 1 edition edition, August 2012.<\/li>\n<li>Peter Flach. Machine Learning: The Art and Science of Algorithms that Make Sense of Data . Cambridge University Press, Cambridge ; New York, 1 edition edition, November 2012.<\/li>\n<li>Christopher Bishop. Pattern Recognition and Machine Learning . Springer, New York, October 2007.<\/li>\n<li>Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. An Introduction to Statistical Learning: with Applications in R . Springer, 1st ed. 2013. corr. 4th printing 2014<\/li>\n<li>Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin. Learning From Data . AMLBook, S.l., March 2012.<\/li>\n<li>Brett Lantz. Machine Learning with R . Packt Publishing, Birmingham, October 2013.<\/li>\n<li>Simon O. Haykin. Neural Networks and Learning Machines . Prentice Hall, New York, 3 edition edition, November 2008.<\/li>\n<li>Ani Adhikari &amp; John DeNero,\u00a0<a href=\"http:\/\/artint.info\/\" target=\"_blank\" rel=\"noopener\">Artificial Intelligence: Foundations of Computational Agents, second edition, Cambridge University Press, 2017<\/a><\/li>\n<li>Voc\u00ea pode pesquisar livros relevantes no acervo da <a href=\"http:\/\/biblioteca.cefet-rj.br\/\">Biblioteca do CEFET\/RJ<\/a>.<\/li>\n<\/ul>\n<p>Livros de interesse geral sobre Aprendizado de M\u00e1quina<\/p>\n<ul>\n<li>Nick Bostrom, <a href=\"https:\/\/www.amazon.com\/Superintelligence-Dangers-Strategies-Nick-Bostrom\/dp\/0198739834\">Superintelligence: Paths, Dangers, Strategies<\/a>, 2014.<\/li>\n<li>Pedro Domingos,\u00a0<a href=\"https:\/\/www.amazon.com\/Master-Algorithm-Ultimate-Learning-Machine\/dp\/0465065708\/ref=pd_bxgy_14_img_2?_encoding=UTF8&amp;psc=1&amp;refRID=8ETNCQKT3X406VVJ3JV9\">The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World<\/a>, 2015.<\/li>\n<li>Jimmy Soni &amp; Rob Goodman, <a href=\"http:\/\/www.simonandschuster.com\/books\/A-Mind-at-Play\/Jimmy-Soni\/9781476766683\">A Mind at Play: How Claude Shannon Invented the Information Age<\/a>, 2017.<\/li>\n<\/ul>\n<hr \/>\n","protected":false},"excerpt":{"rendered":"<p>&nbsp; &nbsp; &nbsp; Cursos Mestrado em Ci\u00eancia da Computa\u00e7\u00e3o Local\/hor\u00e1rio Bloco E, 5o andar, sala E-522 Dia\/hor\u00e1rio: 5as-feiras, das 13:25h \u00e0s 17:00h Apresenta\u00e7\u00e3o Aprendizado de M\u00e1quina (Machine Learning) \u00e9 um campo de estudo da Intelig\u00eancia Artificial cujo objeto de estudo s\u00e3o sistemas que podem aprender a realizar alguma tarefa por meio de experi\u00eancias. Neste curso, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-767","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/pages\/767","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/comments?post=767"}],"version-history":[{"count":43,"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/pages\/767\/revisions"}],"predecessor-version":[{"id":960,"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/pages\/767\/revisions\/960"}],"wp:attachment":[{"href":"https:\/\/eic.cefet-rj.br\/~ebezerra\/wp-json\/wp\/v2\/media?parent=767"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}