{"id":198,"date":"2020-09-06T11:46:36","date_gmt":"2020-09-06T11:46:36","guid":{"rendered":"http:\/\/www.keithdillon.com\/?page_id=198"},"modified":"2020-09-06T13:37:43","modified_gmt":"2020-09-06T13:37:43","slug":"math-for-data-science-spring-2020","status":"publish","type":"page","link":"https:\/\/www.keithdillon.com\/index.php\/math-for-data-science-spring-2020\/","title":{"rendered":"Math for Data Science &#8211; Spring 2020"},"content":{"rendered":"<h1>Overview<\/h1>\n<p>This is a hands-on class surveying a range of mathematical methods for data science, with an emphasis on solving problems with cutting-edge software packages.\u00a0 An understanding of basic linear algebra and probability is needed, as well as programming skills. Python will be used.<\/p>\n<h1>Slides<\/h1>\n<ol>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math01_Introduction.slides.html\">Introduction<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math02_ClassicLinAlgSoftware.slides.html\">Classical linear algebra software<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math03_LinAlg.slides.html\">Linear algebra highlights<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math03_Norms.slides.html\">Norms, Distances, and Statistics<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math04_SVD.slides.html\">Singular Value Decomposition<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math06_Tensors.slides.html\">Vectorization and Tensors<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math07_SpectralNetworks.slides.html\">Networks and graph spectral methods<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math08_GaussianGraphicalModels.slides.html\">Gaussian graphical models<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math10_MatrixCalculus.slides.html\">Matrix Calculus<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math11_GradientDescent.slides.html\">Gradient descent optimization<\/a><\/li>\n<li><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/Math12_Tensorflow_TF2_v1.slides.html\">Computational graphs with Tensorflow<\/a><\/li>\n<\/ol>\n<p><a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/ScalableMathSW.html\">yet more scalable numerical math software<\/a><br \/>\n<a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/tutorials_PyTorch.html\">PyTorch tutorial<\/a><br \/>\n<a href=\"https:\/\/www.keithdillon.com\/classes\/UNH\/6001-02\/tutorials_TensorFlow20.html\">Tensorflow tutorial<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Overview This is a hands-on class surveying a range of mathematical methods for data science, with an emphasis on solving problems with cutting-edge software packages.\u00a0 An understanding of basic linear algebra and probability is needed, as well as programming skills.<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages\/198"}],"collection":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/comments?post=198"}],"version-history":[{"count":14,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages\/198\/revisions"}],"predecessor-version":[{"id":227,"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/pages\/198\/revisions\/227"}],"wp:attachment":[{"href":"https:\/\/www.keithdillon.com\/index.php\/wp-json\/wp\/v2\/media?parent=198"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}