{"id":21518,"date":"2020-05-21T12:32:14","date_gmt":"2020-05-21T16:32:14","guid":{"rendered":"https:\/\/vieux.ivado.ca\/?page_id=21518"},"modified":"2020-07-22T14:14:10","modified_gmt":"2020-07-22T18:14:10","slug":"machine-learning-applied-to-finance-and-insurance-workshop","status":"publish","type":"page","link":"https:\/\/vieux.ivado.ca\/en\/machine-learning-applied-to-finance-and-insurance-workshop\/","title":{"rendered":"IVADO Workshop"},"content":{"rendered":"<p>[vc_row][vc_column][vc_column_text css_animation=&#8221;none&#8221;]<img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-21658\" src=\"https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn.jpg\" alt=\"\" width=\"1347\" height=\"459\" srcset=\"https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn.jpg 1347w, https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn-300x102.jpg 300w, https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn-1024x349.jpg 1024w, https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn-768x262.jpg 768w, https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn-400x136.jpg 400w, https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn-700x239.jpg 700w, https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/IVADO_Finance-workshop_v3_646X220_LinkedIn-120x41.jpg 120w\" sizes=\"(max-width: 1347px) 100vw, 1347px\" \/>[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column el_class=&#8221;width-100-240&#8243; css=&#8221;.vc_custom_1555345720852{margin-top: 0px !important;padding-top: 0px !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text css=&#8221;.vc_custom_1590422164439{margin-bottom: 8px !important;}&#8221;]<\/p>\n<h4><strong><span style=\"color: #0071ba;\">June 30, 2020 &#8211; September 3, 2020 | ONLINE (English)<\/span><\/strong><\/h4>\n<h5><strong><span style=\"color: #0071ba;\">Tuesdays &amp; Thursdays, 4PM &#8211; 5:45PM<br \/>\n<\/span><\/strong><\/h5>\n<p>[\/vc_column_text][vc_empty_space][\/vc_column][\/vc_row][vc_row equal_height=&#8221;yes&#8221; el_class=&#8221;naked clearboth&#8221; css=&#8221;.vc_custom_1554726987628{margin-top: -40px !important;}&#8221;][vc_column][vc_empty_space][vc_tta_tabs][vc_tta_section i_type=&#8221;openiconic&#8221; i_icon_openiconic=&#8221;vc-oi vc-oi-mic&#8221; add_icon=&#8221;true&#8221; title=&#8221;About&#8221; tab_id=&#8221;About&#8221;][vc_empty_space height=&#8221;30px&#8221;][vc_icon type=&#8221;openiconic&#8221; icon_openiconic=&#8221;vc-oi vc-oi-mic&#8221; color=&#8221;custom&#8221; size=&#8221;lg&#8221; align=&#8221;center&#8221; css_animation=&#8221;none&#8221; custom_color=&#8221;#ff671f&#8221; css=&#8221;.vc_custom_1554316743716{margin-bottom: 0px !important;padding-bottom: 0px !important;}&#8221;][vc_column_text el_class=&#8221;h3-souligne&#8221;]<\/p>\n<h3 style=\"text-align: center;\"><strong>About<\/strong><\/h3>\n<p>[\/vc_column_text][vc_empty_space height=&#8221;15px&#8221;][vc_row_inner][vc_column_inner width=&#8221;1\/2&#8243;][vc_column_text css_animation=&#8221;fadeInLeft&#8221;]<\/p>\n<h3>Language<\/h3>\n<p>This workshop will be given in English.[\/vc_column_text][vc_column_text css_animation=&#8221;fadeInLeft&#8221;]<\/p>\n<h3>Description<\/h3>\n<p>The Fin-ML\/IVADO Online Workshop is a practical training in machine learning, applied to concrete problems in investments, banking and insurance. Over each week, the workshop will consist of theory in one session, followed by a problem-solving session. There may be work to complete between the sessions. This online workshop will take place over a 10 week period, 1.5 hour per session with a 15 minute break.[\/vc_column_text][vc_column_text css_animation=&#8221;fadeInLeft&#8221;]<\/p>\n<h3>Target Audience<\/h3>\n<p>Master&#8217;s and PhD students and professionals with quantitative training who want to learn about new technologies in data science, machine learning and operations research, with examples applied to problems in investments, banking and insurance.<\/p>\n<p>*The concepts may be interesting to technical professionals that are not from the finance world, although examples and datasets will come from this environment.[\/vc_column_text][vc_column_text css_animation=&#8221;fadeInLeft&#8221;]<\/p>\n<h3><b>Prerequisites<\/b><\/h3>\n<p>Knowledge of Mathematics &amp; Statistics (Linear Algebra, Probability and Information Theory, Numerical Computation), and Programming (ideally Python) is strongly recommended. The participants can familiarize themselves with Chapters 2 to 4 of the Deep Learning book by Ian Goodfellow and Yoshua Bengio and Aaron Courville (available online <a href=\"http:\/\/deeplearningbook.org\">deeplearningbook.org<\/a>)[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/2&#8243;][vc_column_text css_animation=&#8221;fadeInRight&#8221;]<\/p>\n<h3>Objectives<\/h3>\n<ul>\n<li>Introduce students and professionals to new technologies in machine learning, that are most relevant in the financial sector;<\/li>\n<li>Develop an understanding of the challenges and issues of data science applied to investments, banking and insurance;<\/li>\n<li>Learn to use computer tools to solve concrete problems;<\/li>\n<li>Encourage interdisciplinary knowledge sharing.<\/li>\n<\/ul>\n<p>[\/vc_column_text][vc_column_text css_animation=&#8221;fadeInRight&#8221;]<\/p>\n<h3>Organizers<\/h3>\n<ul>\n<li><a href=\"https:\/\/www.manuelmorales.org\/\">Manuel Morales<\/a>, Associate Professor, Universit\u00e9 de Montr\u00e9al, Director of Fin-ML<\/li>\n<li><a href=\"https:\/\/vieux.ivado.ca\/en\/person\/rheia-khalaf\/\" target=\"_blank\" rel=\"noopener noreferrer\">Rheia Khalaf<\/a>, Director of Collaborative Research &amp; Partnerships, Fin-ML<\/li>\n<li><a href=\"https:\/\/vieux.ivado.ca\/en\/person\/nathalie-sanon\/\" target=\"_blank\" rel=\"noopener noreferrer\">Nathalie Sanon<\/a>, Head of IVADO training program<\/li>\n<\/ul>\n<p>[\/vc_column_text][vc_column_text css_animation=&#8221;fadeInRight&#8221;]<\/p>\n<h3>Registration<\/h3>\n<p>Professionals:&nbsp;$1300 + tx<br \/>\nStudents:&nbsp;$500 + tx[\/vc_column_text]<div class=\" ubtn-ctn-center \"><a class=\"ubtn-link ult-adjust-bottom-margin ubtn-center ubtn-normal \" href=\"https:\/\/www.eventbrite.ca\/e\/machine-learning-applied-to-finance-and-insurance-workshop-online-registration-105442140280\" ><button type=\"button\" id=\"ubtn-2820\" onclick=\"this.target=&#039;_blank&#039;\" class=\"ubtn ult-adjust-bottom-margin ult-responsive ubtn-normal ubtn-no-hover-bg  none  ubtn-sep-icon ubtn-sep-icon-left-push  ubtn-center   tooltip-69dc4604a88f8 ubtn-tooltip bottom\" data-toggle=\"tooltip\" data-placement=\"bottom\" title=\"French, members only\" data-hover=\"\" data-border-color=\"\" data-bg=\"#ff8139\" data-hover-bg=\"\" data-border-hover=\"\" data-shadow-hover=\"\" data-shadow-click=\"none\" data-shadow=\"\" data-shd-shadow=\"\"  data-ultimate-target='#ubtn-2820'  data-responsive-json-new='{\"font-size\":\"desktop:24px;\",\"line-height\":\"\"}'  style=\"font-weight:bold;border:none;background: #ff8139;color: #ffffff;\"><span class=\"ubtn-data ubtn-icon\"><i class=\"Defaults-edit pencil-square-o\" style=\"font-size:32px;color:;\"><\/i><\/span><span class=\"ubtn-hover\" style=\"background-color:\"><\/span><span class=\"ubtn-data ubtn-text \" >Registration<\/span><\/button><\/a><\/div><script>\r\n\t\t\t\t\tjQuery(function () {\r\n\t\t\t\t\t\tjQuery(\".tooltip-69dc4604a88f8\").bsf_tooltip();\r\n\t\t\t\t\t})\r\n\t\t\t\t<\/script>[vc_column_text css_animation=&#8221;fadeInRight&#8221;]<a href=\"https:\/\/vieux.ivado.ca\/evenement\/machine-learning-applied-to-finance-and-insurance-workshop\/\">Click here to see event<\/a>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner disable_element=&#8221;yes&#8221;][vc_column_inner width=&#8221;1\/2&#8243;][vc_column_text css_animation=&#8221;fadeInUp&#8221;]<\/p>\n<p style=\"text-align: center;\">May 13-17, 2019: The workshop will be held in\u00a0<strong>English<\/strong>\u00a0at HEC Montr\u00e9al (PWC, C\u00f4te Ste-Catherine).<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/2&#8243;][vc_column_text css_animation=&#8221;fadeInUp&#8221;]<\/p>\n<p style=\"text-align: center;\">June 10-14, 2019:\u00a0The workshop will be held in\u00a0<b>French\u00a0<\/b>at HEC Montr\u00e9al (PWC, C\u00f4te Ste-Catherine).<\/p>\n<p>[\/vc_column_text][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243;][\/vc_column_inner][\/vc_row_inner][\/vc_tta_section][vc_tta_section title=&#8221;Trainers&#8221; tab_id=&#8221;trainers&#8221;][vc_empty_space height=&#8221;30px&#8221;][vc_icon type=&#8221;entypo&#8221; icon_entypo=&#8221;entypo-icon entypo-icon-users&#8221; color=&#8221;custom&#8221; size=&#8221;lg&#8221; align=&#8221;center&#8221; custom_color=&#8221;#ff671f&#8221;][vc_column_text]<\/p>\n<h3 style=\"text-align: center;\"><strong>Confirmed Trainers<\/strong><\/h3>\n<p>[\/vc_column_text][vc_empty_space height=&#8221;15px&#8221;][vc_row_inner][vc_column_inner width=&#8221;1\/4&#8243;][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243; css=&#8221;.vc_custom_1590431589172{background-image: url(https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/Aden-Houssein.jpg?id=21630) !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text]<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/mila.quebec\/en\/person\/aboubaker-aden-houssein\/\">Aden Houssein Aboubaker<\/a><br \/>\nMSc. Maths and Computer Science in Laval University (2018)<br \/>\nStudent in Artificial Intelligence in Mila-Montreal University<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/4&#8243;][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243; css=&#8221;.vc_custom_1590431843564{background-image: url(https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/Alexandre-Carbonneau.jpg?id=21636) !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text]<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.linkedin.com\/in\/alexandre-carbonneau-26945698\/\">Alexandre Carbonneau<\/a><br \/>\nPhD student in financial mathematics at Concordia University<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/4&#8243;][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243; css=&#8221;.vc_custom_1590432045951{background-image: url(https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/Didier-Chetelat.jpg?id=21638) !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text]<\/p>\n<p style=\"text-align: center;\"><a href=\"http:\/\/www.didierchetelat.com\/\">Didier Ch\u00e9telat<\/a><br \/>\nResearcher<br \/>\nPolytechnique Montr\u00e9al<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/4&#8243;][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243; css=&#8221;.vc_custom_1590432210806{background-image: url(https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2019\/08\/Jonathan-Guymont.jpg?id=15448) !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text]<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.linkedin.com\/in\/jonathan-guymont-69142598\/?locale=en_US\">Jonathan Guymont<\/a><br \/>\nM. Sc. Candidate in Machine Learning<br \/>\nMILA<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][vc_row_inner][vc_column_inner width=&#8221;1\/4&#8243;][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243; css=&#8221;.vc_custom_1590432624279{background-image: url(https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/profil_picture.png?id=21642) !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text]<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.linkedin.com\/in\/alexandrenguyen1\/\">Alexandre Nguyen<\/a><br \/>\nMachine Learning Consultant<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/4&#8243;][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243; css=&#8221;.vc_custom_1590434975108{background-image: url(https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/Marie-Eve-Mallette.jpg?id=21646) !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text]<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.linkedin.com\/in\/marie-%C3%A8ve-malette-92015689\/\">Marie-\u00c8ve Malette<\/a><br \/>\nAI Scientist<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/4&#8243;][vc_empty_space height=&#8221;0px&#8221; el_class=&#8221;padding-120&#8243; css=&#8221;.vc_custom_1590433220606{background-image: url(https:\/\/vieux.ivado.ca\/wp-content\/uploads\/2020\/05\/Cedric-Poutre.jpg?id=21648) !important;}&#8221;][vc_empty_space height=&#8221;10px&#8221;][vc_column_text]<\/p>\n<p style=\"text-align: center;\"><a href=\"https:\/\/www.linkedin.com\/in\/cedricpoutre\/\">C\u00e9dric Poutr\u00e9<\/a><br \/>\nPhD candidate in financial mathematics at the University of Montreal and research assistant in high-frequency trading at IVADO<\/p>\n<p>[\/vc_column_text][\/vc_column_inner][vc_column_inner width=&#8221;1\/4&#8243;][\/vc_column_inner][\/vc_row_inner][\/vc_tta_section][vc_tta_section i_type=&#8221;openiconic&#8221; i_icon_openiconic=&#8221;vc-oi vc-oi-calendar-inv&#8221; add_icon=&#8221;true&#8221; title=&#8221;Program&#8221; tab_id=&#8221;Program&#8221; el_class=&#8221;bouton-programme&#8221;][\/vc_tta_section][\/vc_tta_tabs][\/vc_column][\/vc_row][vc_row css_animation=&#8221;none&#8221; el_class=&#8221;orange ferme&#8221; css=&#8221;.vc_custom_1554317805323{margin-top: -20px !important;}&#8221;][vc_column][vc_empty_space][vc_icon type=&#8221;openiconic&#8221; icon_openiconic=&#8221;vc-oi vc-oi-calendar-inv&#8221; color=&#8221;custom&#8221; size=&#8221;lg&#8221; align=&#8221;center&#8221; css_animation=&#8221;none&#8221; custom_color=&#8221;#ff671f&#8221; css=&#8221;.vc_custom_1554301958146{margin-bottom: 0px !important;padding-bottom: 0px !important;}&#8221;][vc_column_text el_class=&#8221;h3-souligne&#8221;]<\/p>\n<h3 style=\"text-align: center;\"><strong>Program<\/strong><\/h3>\n<p>[\/vc_column_text][vc_column_text el_class=&#8221;h3-souligne&#8221;]<strong>Theme 1<\/strong> &#8211; Weeks 1 &#8211; 2: Introduction to machine learning<\/p>\n<p><strong>Theme 2<\/strong> &#8211; Weeks 3 &#8211; 4 &#8211; 5: Introduction to deep learning in investments, banking and insurance<\/p>\n<p><strong>Theme 3 <\/strong>&#8211; Weeks 5 &#8211; 6: Machine learning in time series forecasting<\/p>\n<p><strong>Theme 4 <\/strong>&#8211; Weeks 7 &#8211; 8: Introduction to Natural Language Processing in investments, banking and insurance<\/p>\n<p><strong>Theme 5<\/strong> &#8211; Weeks 9 &#8211; 10: Reinforcement Learning in investments, banking and insurance[\/vc_column_text][vc_empty_space height=&#8221;15px&#8221;][vc_tta_tabs active_section=&#8221;1&#8243;][vc_tta_section title=&#8221;Theme 1&#8243; tab_id=&#8221;Theme-1&#8243;][vc_empty_space][vc_column_text]<strong>Theme 1: <\/strong>Introduction to machine learning<\/p>\n<p><strong><u>Week 1\u00a0<\/u><\/strong><\/p>\n<p><strong>Theory: <\/strong><em>C\u00e9dric Poutr\u00e9<\/em><\/p>\n<ul>\n<li>Types of learning: supervised, unsupervised and reinforced<\/li>\n<li>Introduction\n<ul>\n<li>Regression: Machine learning models vs. statistical approaches<\/li>\n<\/ul>\n<\/li>\n<li>Good practices: Overfitting and regularization<\/li>\n<li>Good practices: Experimental design<\/li>\n<\/ul>\n<p><strong>Tutorial:<\/strong> <em>Didier Ch\u00e9telat<\/em><\/p>\n<ul>\n<li>Exploratory data analysis of an insurance dataset<\/li>\n<li>Regression models<\/li>\n<li>Generalisation and regularisation<\/li>\n<\/ul>\n<p><strong><u>Week 2<\/u><\/strong><u>\u00a0<\/u><\/p>\n<p><strong>Theory:<\/strong> <em>C\u00e9dric Poutr\u00e9<\/em><\/p>\n<ul>\n<li>Introduction: Classification\n<ul>\n<li>Traditional approaches: SVM, Random Forests, etc<\/li>\n<li>Modern approaches: neural networks<\/li>\n<\/ul>\n<\/li>\n<li>Introduction: Clustering<\/li>\n<li>Traditional approaches: K-means<\/li>\n<\/ul>\n<p><strong>Tutorial:<\/strong><em> Didier Ch\u00e9telat<\/em><\/p>\n<ul>\n<li>Classification models<\/li>\n<li>Unsupervised analysis<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_tta_section][vc_tta_section title=&#8221;Theme 2&#8243; tab_id=&#8221;Theme-2&#8243;][vc_empty_space][vc_column_text]<strong>Theme 2 &#8211;<\/strong> Introduction to deep learning in investments, banking and insurance<\/p>\n<p><strong><u>Week 3<\/u><\/strong><\/p>\n<p><strong>Theory:<\/strong><em> Alexandre Nguyen<\/em><\/p>\n<ul>\n<li>Introduction: Forecasting problem<\/li>\n<li>Multilayered Perceptron<\/li>\n<li>Introduction to Deep Neural Network Architectures (CNN, AE)<\/li>\n<\/ul>\n<p><strong>Tutorial:<\/strong> <em>Aden Houssein Aboubaker<\/em><\/p>\n<ul>\n<li>Comparison between ML and DL applied in Banking (Fraud Detection):\n<ul>\n<li>Fraud detection dataset: we will do following steps: Exploratory Data Analysis, Data Preprocessing, Model Evaluation and Selection based on good metric adapted to the situation,<\/li>\n<li>We will focus on methodological approaches to handle efficiently the problem of unbalanced datasets in a binary classification context for Fraud Detection,<\/li>\n<li>Indeed, the problem of unbalanced data is very frequent in the industry and this is why it is now necessary to have in its Data Scientist toolbox the techniques that allow to remedy this,<\/li>\n<li>We will see that there are several solutions to remedy this imbalance problem such as: (1.a) choosing the right metric to monitor, (1.b) solutions at the algorithmic level (e.g. introducing a penalty in the cost function, cost-sensitive learning&#8230;), (2) selecting a good threshold (e.g. by optimizing threshold using precision\/recall graphs), (3) solutions at the data level (under\/oversampling, synthetic data&#8230;),, and (4) anomaly detection (e.g. Auto-encoders, Isolation Forest&#8230;).<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong><u>Week 4<\/u><\/strong><\/p>\n<p><strong>Tutorial<\/strong>: <em>Aden Houssein Aboubaker<\/em><\/p>\n<ul>\n<li>Deep \/ Representation Learning applied in Insurance (Claim forecasting):\n<ul>\n<li>How representation learning could allow to boost models<\/li>\n<li>How to correctly apply neural network in context of mixed tabular data<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><strong>Theory<\/strong>: <em>Marie-\u00c8ve Malette<\/em><\/p>\n<ul>\n<li>Generative models\n<ul>\n<li>Variational Auto-encoders<\/li>\n<li>Adversarial networks (GAN)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><span style=\"text-decoration: underline;\"><strong>Week 5<\/strong><\/span> (1 session)<\/p>\n<p><strong>Tutorial<\/strong>: <em>Marie-\u00c8ve Malette<\/em><\/p>\n<ul>\n<li>Conditional variational autoencoders for event occurrence probability estimation<\/li>\n<li>Variational Autoencoders in Insurance<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_tta_section][vc_tta_section title=&#8221;Theme 3&#8243; tab_id=&#8221;Theme-3&#8243;][vc_empty_space][vc_column_text]<strong>Theme 3 <\/strong>&#8211; Machine learning in time series forecasting<\/p>\n<p><strong><u>Week 5<\/u><\/strong>\u00a0(1 session)<strong><u><br \/>\n<\/u><\/strong><\/p>\n<p><strong>Theory<\/strong>: <em>Alex Nguyen<\/em><\/p>\n<ul>\n<li>Introduction to recurrent neural networks (continued) (RNN, LSTM, GRU)<\/li>\n<li>Forecasting problem<\/li>\n<\/ul>\n<p><strong><u>Week 6<\/u><\/strong><\/p>\n<p><strong>Tutorial<\/strong>: <em>Jonathan Guymont<\/em><\/p>\n<ul>\n<li>LSTM, GRU for times series prediction<\/li>\n<li>RNN for times series prediction<\/li>\n<li>Use case 1<\/li>\n<\/ul>\n<p><strong>Tutorial<\/strong>: <em>Jonathan Guymont<\/em><\/p>\n<ul>\n<li>LSTM, GRU for times series prediction<\/li>\n<li>RNN for times series prediction<\/li>\n<li>Use case 2<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_tta_section][vc_tta_section title=&#8221;Theme 4&#8243; tab_id=&#8221;Theme-4&#8243;][vc_empty_space][vc_column_text]<b>Theme 4 <\/b>&#8211; Introduction to Natural Language Processing in investments, banking and insurance<\/p>\n<p><b>Week 7<\/b><\/p>\n<p><b>Theory:<\/b> <i>Alexandre Nguyen<\/i><\/p>\n<ul>\n<li>Introduction to classical and modern NLP<\/li>\n<li>Text processing<\/li>\n<li>Language representations<\/li>\n<\/ul>\n<p><b>Tutorial:<\/b> <i>Jonathan Guymont<\/i><\/p>\n<ul>\n<li>Sentiment analysis\n<ul>\n<li>Application of convolutional neural networks (CNN)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><b>Week 8\u00a0<\/b><\/p>\n<p><b>Theory: <\/b><i>Alexandre Nguyen<\/i><\/p>\n<ul>\n<li>Advanced language models<\/li>\n<li>Recent development<\/li>\n<li>Applications<\/li>\n<\/ul>\n<p><b>Tutorial:<\/b> <i>Jonathan Guymont<\/i><\/p>\n<ul>\n<li>Anomaly detection\n<ul>\n<li>Generative models<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_tta_section][vc_tta_section title=&#8221;Theme 5&#8243; tab_id=&#8221;Theme-5&#8243;][vc_empty_space][vc_column_text]<b>Theme 5<\/b>&#8211; Reinforcement Learning in investments, banking and insurance<\/p>\n<p><b>Week 9<\/b><\/p>\n<p><b>Theory:<\/b> <i>Alexandre Carbonneau<\/i><\/p>\n<ul>\n<li>Introduction: learning by reinforcement\n<ul>\n<li>What is the \u2018reinforcement learning problem\u2019?<\/li>\n<li>One popular reinforcement learning approach: Q-learning<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><b>Tutorial:<\/b> <i>Didier Ch\u00e9telat<\/i><\/p>\n<ul>\n<li>Presentation of a financial trading environment<\/li>\n<li>Tabular Q-learning<\/li>\n<\/ul>\n<p><b>Week 10<\/b><\/p>\n<p><b>Theory:<\/b> <i>Alexandre Carbonneau<\/i><\/p>\n<ul>\n<li>Reinforcement learning for large-scale problems\n<ul>\n<li>Pitfalls of tabular methods of reinforcement learning<\/li>\n<li>Function approximators for value and action-value functions<\/li>\n<li>Introduction to deep Q-networks<\/li>\n<li>Real-life applications of deep reinforcement learning<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><b>Tutorial:<\/b> <i>Didier Ch\u00e9telat<\/i><\/p>\n<ul>\n<li>Q-learning with linear function approximation<\/li>\n<li>Experience replay<\/li>\n<\/ul>\n<p>[\/vc_column_text][\/vc_tta_section][\/vc_tta_tabs][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_column_text css_animation=&#8221;none&#8221;][\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column el_class=&#8221;width-100-240&#8243; 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