{"id":50,"date":"2023-02-07T15:47:13","date_gmt":"2023-02-07T20:47:13","guid":{"rendered":"https:\/\/new.umaine.edu\/ai-bootcamps\/?page_id=50"},"modified":"2024-09-30T15:54:46","modified_gmt":"2024-09-30T19:54:46","slug":"event_details","status":"publish","type":"page","link":"https:\/\/umaine.edu\/ai-bootcamps\/event_details\/","title":{"rendered":"Event Details"},"content":{"rendered":"\n<p>This bootcamp is a joint effort between the Sekeh Lab at the University of Maine, and Northeastern\u2019s Roux Institute.<\/p>\n\n\n<style>.kb-image50_7d41b8-8a.kb-image-is-ratio-size, .kb-image50_7d41b8-8a .kb-image-is-ratio-size{max-width:175px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_7d41b8-8a.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_7d41b8-8a .kb-image-is-ratio-size{align-self:unset;}.kb-image50_7d41b8-8a figure{max-width:175px;}.kb-image50_7d41b8-8a .image-is-svg, .kb-image50_7d41b8-8a .image-is-svg img{width:100%;}.kb-image50_7d41b8-8a .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image50_7d41b8-8a\"><figure class=\"alignleft size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"250\" height=\"250\" src=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/logo-e1679062552644.png\" alt=\"Collaboration Logo of Sekeh Lab, UMaine, and The Roux Institute\" class=\"kb-img wp-image-247\" srcset=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/logo-e1679062552644.png 250w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/logo-e1679062552644-150x150.png 150w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/logo-e1679062552644-105x105.png 105w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/logo-e1679062552644-32x32.png 32w\" sizes=\"auto, (max-width: 320px) 85vw, (max-width: 768px) 67vw, (max-width: 1024px) 62vw,250px\" \/><\/figure><\/div>\n\n\n\n<p>Graduate students from the Sekeh Lab will present a series of tutorials, with Faculty from Universities and Principle Scientists from Industries giving talks on Deep Learning and AI.<\/p>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-50_06c0f1-e7 .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-50_06c0f1-e7 .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-50_06c0f1-e7\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\"\/><\/div><\/div>\n\n\n\n<p><strong>Tutorial #1:<\/strong> Introduction to Machine Learning (Lecture)<br><strong>Instructor<\/strong>: Mahsa Mozafarinia<\/p>\n\n\n<style>.kb-image50_084d6a-f7.kb-image-is-ratio-size, .kb-image50_084d6a-f7 .kb-image-is-ratio-size{max-width:175px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_084d6a-f7.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_084d6a-f7 .kb-image-is-ratio-size{align-self:unset;}.kb-image50_084d6a-f7 figure{max-width:175px;}.kb-image50_084d6a-f7 .image-is-svg, .kb-image50_084d6a-f7 .image-is-svg img{width:100%;}.kb-image50_084d6a-f7 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image50_084d6a-f7\"><figure class=\"alignleft size-medium\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"300\" src=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/IMG_20230210_132137_186-e1679081975353-300x300.jpg\" alt=\"Mahsa Mozafarinia Photo\" class=\"kb-img wp-image-292\"\/><\/figure><\/div>\n\n\n\n<p>This tutorial covers basic concepts on supervised learning such as classification and regression. The students learn risk function, classifier, loss function, and optimal solutions.&nbsp;<\/p>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-50_044512-72 .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-50_044512-72 .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-50_044512-72\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\"\/><\/div><\/div>\n\n\n\n<p><strong>Tutorial #2:<\/strong> Introduction to Python Programming (Practicum)<br><strong>Instructor:<\/strong> Sepideh Neshatfar<\/p>\n\n\n<style>.kb-image50_8434de-5e.kb-image-is-ratio-size, .kb-image50_8434de-5e .kb-image-is-ratio-size{max-width:175px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_8434de-5e.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_8434de-5e .kb-image-is-ratio-size{align-self:unset;}.kb-image50_8434de-5e figure{max-width:175px;}.kb-image50_8434de-5e .image-is-svg, .kb-image50_8434de-5e .image-is-svg img{width:100%;}.kb-image50_8434de-5e .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image50_8434de-5e\"><figure class=\"alignleft size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"240\" height=\"240\" src=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Sepideh-e1679082114562.jpg\" alt=\"Sepideh Neshatfar Photo\" class=\"kb-img wp-image-231\"\/><\/figure><\/div>\n\n\n\n<p>This tutorial focuses on python programming with introduction to numpy, and SKlearn library. The SKLearn lab will teach students how to import data such as MNIST (via a Google Colab Notebook) with emphasis on how to improve classifier performance, then time for students to try their own classifiers on a separate sentiment analysis task.<\/p>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-50_cabc1c-c1 .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-50_cabc1c-c1 .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-50_cabc1c-c1\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\"\/><\/div><\/div>\n\n\n\n<p><strong>Tutorial #3:<\/strong> Introduction to Neural Network and Backpropagation (Lecture)<br><strong>Instructor:<\/strong> Mary Wisell<\/p>\n\n\n<style>.kb-image50_4c72d6-d6.kb-image-is-ratio-size, .kb-image50_4c72d6-d6 .kb-image-is-ratio-size{max-width:175px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_4c72d6-d6.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_4c72d6-d6 .kb-image-is-ratio-size{align-self:unset;}.kb-image50_4c72d6-d6 figure{max-width:175px;}.kb-image50_4c72d6-d6 .image-is-svg, .kb-image50_4c72d6-d6 .image-is-svg img{width:100%;}.kb-image50_4c72d6-d6 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image50_4c72d6-d6\"><figure class=\"alignleft size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"247\" height=\"247\" src=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Wisell-Headshot-e1679061763608.jpg\" alt=\"Mary Wisell Photo\" class=\"kb-img wp-image-233\" srcset=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Wisell-Headshot-e1679061763608.jpg 247w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Wisell-Headshot-e1679061763608-150x150.jpg 150w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Wisell-Headshot-e1679061763608-105x105.jpg 105w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Wisell-Headshot-e1679061763608-32x32.jpg 32w\" sizes=\"auto, (max-width: 320px) 85vw, (max-width: 768px) 67vw, (max-width: 1024px) 62vw,247px\" \/><\/figure><\/div>\n\n\n\n<p>This tutorial covers an introduction on multiple layer perceptron (MLP), initialization, stochastic gradient descent method, effect of learning rate on convergence, Stopping criteria, and backpropagation rule.&nbsp;<\/p>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-50_cd0395-eb .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-50_cd0395-eb .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-50_cd0395-eb\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\"\/><\/div><\/div>\n\n\n\n<p><strong>Tutorial #4:<\/strong> Deep Neural Network Pytorch Programming (Practicum)<br><strong>Instructor: Soheil Gharatappeh<\/strong><\/p>\n\n\n<style>.kb-image50_ea7ef2-5e.kb-image-is-ratio-size, .kb-image50_ea7ef2-5e .kb-image-is-ratio-size{max-width:175px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_ea7ef2-5e.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_ea7ef2-5e .kb-image-is-ratio-size{align-self:unset;}.kb-image50_ea7ef2-5e figure{max-width:175px;}.kb-image50_ea7ef2-5e .image-is-svg, .kb-image50_ea7ef2-5e .image-is-svg img{width:100%;}.kb-image50_ea7ef2-5e .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image50_ea7ef2-5e\"><figure class=\"alignleft size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"230\" height=\"230\" src=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Soheil-e1679061720373.jpg\" alt=\"Soheil Gharatappeh Photo\" class=\"kb-img wp-image-232\" srcset=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Soheil-e1679061720373.jpg 230w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Soheil-e1679061720373-150x150.jpg 150w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Soheil-e1679061720373-105x105.jpg 105w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Soheil-e1679061720373-32x32.jpg 32w\" sizes=\"auto, (max-width: 320px) 85vw, (max-width: 768px) 67vw, (max-width: 1024px) 62vw,230px\" \/><\/figure><\/div>\n\n\n\n<p>This practicum lab will have a tutorial on PyTorch and how to build feed-forward deep neural nets for the same tasks as in the Sklearn lab (with emphasis on how to improve performance). A part of the tutorial is for students to try to build their own network for the separate classification task.<\/p>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-50_d2e1e1-b7 .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-50_d2e1e1-b7 .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-50_d2e1e1-b7\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\"\/><\/div><\/div>\n\n\n\n<p><strong>Tutorial #5:<\/strong> Convolutional Neural Network (CNN) Pytorch Programming (Practicum)<br><strong>Instructor: <\/strong>Josh Andle<\/p>\n\n\n<style>.kb-image50_892b48-b3.kb-image-is-ratio-size, .kb-image50_892b48-b3 .kb-image-is-ratio-size{max-width:175px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_892b48-b3.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_892b48-b3 .kb-image-is-ratio-size{align-self:unset;}.kb-image50_892b48-b3 figure{max-width:175px;}.kb-image50_892b48-b3 .image-is-svg, .kb-image50_892b48-b3 .image-is-svg img{width:100%;}.kb-image50_892b48-b3 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image50_892b48-b3\"><figure class=\"alignleft size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"250\" height=\"250\" src=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Josh-e1679061517766.jpg\" alt=\"Josh Andle Photo\" class=\"kb-img wp-image-229\" srcset=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Josh-e1679061517766.jpg 250w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Josh-e1679061517766-150x150.jpg 150w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Josh-e1679061517766-105x105.jpg 105w, https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/Josh-e1679061517766-32x32.jpg 32w\" sizes=\"auto, (max-width: 320px) 85vw, (max-width: 768px) 67vw, (max-width: 1024px) 62vw,250px\" \/><\/figure><\/div>\n\n\n\n<p>This practicum lab will have an introductory tutorial on training well-known Convolutional neural networks such as AlexNet, VGG, or ResNet with providing debugging tips and troubleshooting skills. A part of the tutorial is for students to try to train their model for the separate classification task. The students may try to tune a subset of CIFAR10.<\/p>\n\n\n<style>.wp-block-kadence-spacer.kt-block-spacer-50_f2dff4-4f .kt-block-spacer{height:60px;}.wp-block-kadence-spacer.kt-block-spacer-50_f2dff4-4f .kt-divider{border-top-width:1px;height:1px;border-top-color:#eee;width:80%;border-top-style:solid;}<\/style>\n<div class=\"wp-block-kadence-spacer aligncenter kt-block-spacer-50_f2dff4-4f\"><div class=\"kt-block-spacer kt-block-spacer-halign-center\"><hr class=\"kt-divider\"\/><\/div><\/div>\n\n\n\n<p>The bootcamp includes the following talks from members of academia and industry<\/p>\n\n\n<style>.kb-image50_2d3d4f-0a.kb-image-is-ratio-size, .kb-image50_2d3d4f-0a .kb-image-is-ratio-size{max-width:400px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_2d3d4f-0a.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image50_2d3d4f-0a .kb-image-is-ratio-size{align-self:unset;}.kb-image50_2d3d4f-0a figure{max-width:400px;}.kb-image50_2d3d4f-0a .image-is-svg, .kb-image50_2d3d4f-0a .image-is-svg img{width:100%;}.kb-image50_2d3d4f-0a .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image50_2d3d4f-0a\"><figure class=\"alignleft size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"655\" height=\"1024\" src=\"https:\/\/umaine.edu\/ai-bootcamps\/wp-content\/uploads\/sites\/666\/2023\/03\/1675173637880-e1679079192996-655x1024.jpeg\" alt=\"A crowd of attendees watches a panel of speakers being introduced at an A I event.\" class=\"kb-img wp-image-284\"\/><\/figure><\/div>\n\n\n\n<p><strong>Talk 1:<\/strong> Deep Learning with Shallow Data<br><strong>Speaker: <\/strong>Sarah Ostadabbas<\/p>\n\n\n\n<p><strong>Talk 2:<\/strong> Egocentric Audio-Visual Scene Understanding<br><strong>Speaker: <\/strong>Chenliang Xu<\/p>\n\n\n\n<p><strong>Talk 3:<\/strong> This Looks Like That &#8212; Interpretable Deep Learning for Computer Vision and Applications in Medical Image Analysis<br><strong>Speaker: <\/strong>Chaofan Chen<\/p>\n\n\n\n<p><strong>Talk 4:<\/strong> MultiModal ML: The Why and How of Leveraging Multiple Data Modalities<br><strong>Speaker: <\/strong>Suren Kumar<\/p>\n\n\n\n<p><strong>Talk 5:<\/strong> Neural Networks and Inverse Problems<br><strong>Speaker:&nbsp; <\/strong>Paul Hand<\/p>\n\n\n\n<p><strong>Talk 6:<\/strong> AI to AX: Artificial Intelligence to Artificial Experiences<br><strong>Speaker: <\/strong>Nimesha Ranasinghe<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This bootcamp is a joint effort between the Sekeh Lab at the University of Maine, and Northeastern\u2019s Roux Institute. Graduate students from the Sekeh Lab will present a series of tutorials, with Faculty from Universities and Principle Scientists from Industries giving talks on Deep Learning and AI. Tutorial #1: Introduction to Machine Learning (Lecture)Instructor: Mahsa [&hellip;]<\/p>\n","protected":false},"author":2236,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_kad_blocks_custom_css":"","_kad_blocks_head_custom_js":"","_kad_blocks_body_custom_js":"","_kad_blocks_footer_custom_js":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-50","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Event Details - Summer Bootcamp - University of Maine<\/title>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Event Details - Summer Bootcamp - University of Maine\" \/>\n<meta property=\"og:description\" content=\"This bootcamp is a joint effort between the Sekeh Lab at the University of Maine, and Northeastern\u2019s Roux Institute. 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