{"id":10400,"date":"2026-08-10T10:18:41","date_gmt":"2026-08-10T10:18:41","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/oreilly-up-and-running-with-pytorch-2025-3\/"},"modified":"2026-08-10T10:18:41","modified_gmt":"2026-08-10T10:18:41","slug":"oreilly-up-and-running-with-pytorch-2025-3","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/oreilly-up-and-running-with-pytorch-2025-3\/","title":{"rendered":"Oreilly \u2013 Up and Running with PyTorch 2025-3"},"content":{"rendered":"<div class=\"w-post-elm post_content\">\n<h2 dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Description<\/span><\/h2>\n<p dir=\"ltr\" style=\"text-align: left\" data-sourcepos=\"19:1-19:490\"><span style=\"vertical-align: inherit\">Up and Running with PyTorch course. This course teaches the basics of working with PyTorch, one of the powerful deep learning frameworks. It begins with an introduction to PyTorch and its role in deep learning research, then explains basic concepts such as tensors as building blocks of data and how to work with them. It also teaches the importance of computational graphs and the backpropagation mechanism using the torch.autograd module. One of the key sections is optimizing computations using GPUs and introducing learning algorithms such as Gradient Descent and Stochastic Gradient Descent (SGD). Next, the concepts are put into practice by implementing a simple linear regression model. Then, the structure of perceptrons and neurons as the basic units of neural networks is introduced, and a multilayer neural network (MLP) is created using the torch.nn module. The course concludes with a comprehensive review of the material presented, paving the way for learning more complex models.<\/span><\/p>\n<h3 dir=\"ltr\" style=\"text-align: left\" data-sourcepos=\"21:1-21:25\"><span style=\"vertical-align: inherit\">What you will learn:<\/span><\/h3>\n<ul dir=\"ltr\" style=\"text-align: left\" data-sourcepos=\"23:1-33:0\">\n<li data-sourcepos=\"23:1-23:53\"><span style=\"vertical-align: inherit\">Understand the basic concepts of PyTorch and deep learning frameworks<\/span><\/li>\n<li data-sourcepos=\"24:1-24:27\"><span style=\"vertical-align: inherit\">Working with Tensors in PyTorch<\/span><\/li>\n<li data-sourcepos=\"25:1-25:50\"><span style=\"vertical-align: inherit\">Understanding the concept of Computational Graphs and Backpropagation<\/span><\/li>\n<li data-sourcepos=\"26:1-26:60\"><span style=\"vertical-align: inherit\">Using torch.autograd for automatic differentiation<\/span><\/li>\n<li data-sourcepos=\"27:1-27:24\"><span style=\"vertical-align: inherit\">Working with GPUs in PyTorch<\/span><\/li>\n<li data-sourcepos=\"28:1-28:37\"><span style=\"vertical-align: inherit\">Understanding the components of a learning algorithm<\/span><\/li>\n<li data-sourcepos=\"29:1-29:45\"><span style=\"vertical-align: inherit\">Implementing a Linear Regression Model with PyTorch<\/span><\/li>\n<li data-sourcepos=\"30:1-30:33\"><span style=\"vertical-align: inherit\">Understanding the concept of Perceptrons and Neurons<\/span><\/li>\n<li data-sourcepos=\"31:1-31:52\"><span style=\"vertical-align: inherit\">Using layers and activation functions with torch.nn<\/span><\/li>\n<li data-sourcepos=\"32:1-33:0\"><span style=\"vertical-align: inherit\">Building Multilayer Feedforward (MLP) Neural Networks<\/span><\/li>\n<\/ul>\n<h3 dir=\"ltr\" style=\"text-align: left\" data-sourcepos=\"34:1-34:32\"><span style=\"vertical-align: inherit\">Who is this course suitable for?<\/span><\/h3>\n<ul dir=\"ltr\" style=\"text-align: left\" data-sourcepos=\"36:1-40:0\">\n<li data-sourcepos=\"36:1-36:61\"><span style=\"vertical-align: inherit\">People who are just getting acquainted with deep learning and PyTorch.<\/span><\/li>\n<li data-sourcepos=\"37:1-37:86\"><span style=\"vertical-align: inherit\">Developers who want to use PyTorch to build deep learning models.<\/span><\/li>\n<li data-sourcepos=\"38:1-38:79\"><span style=\"vertical-align: inherit\">Students and researchers interested in learning the fundamental concepts of deep learning.<\/span><\/li>\n<li data-sourcepos=\"39:1-40:0\"><span style=\"vertical-align: inherit\">Anyone who wants to gain a practical understanding of how neural networks work.<\/span><\/li>\n<\/ul>\n<h3 dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Up and Running with PyTorch course details<\/span><\/h3>\n<ul dir=\"ltr\" style=\"text-align: left\">\n<li><span style=\"vertical-align: inherit\">Publisher: <\/span><a href=\"https:\/\/href.li\/?https:\/\/www.oreilly.com\/library\/view\/up-and-running\/9780135446614\/?_gl=1*ryyvmw*_ga*MTU4NjE0OTc3OC4xNzEyMjIyNDU3*_ga_092EL089CH*czE3NDc0MDc1OTckbzkyJGcxJHQxNzQ3NDA3Njk2JGo1OSRsMCRoMA..\" target=\"_blank\" rel=\"noopener\"><span style=\"vertical-align: inherit\">Oreilly<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Instructor: <\/span><a href=\"https:\/\/downloadlynet.ir\/tag\/jonathan-dinu\/\"><span style=\"vertical-align: inherit\">Jonathan Dinu<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Training level: Beginner to advanced<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Training duration: 2 hours and 55 minutes<\/span><\/li>\n<\/ul>\n<h3 dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Course headings<\/span><\/h3>\n<div class=\"ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm\" dir=\"ltr\" style=\"text-align: left\">\n<ul>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Introduction <\/span><br \/><span style=\"vertical-align: inherit\">Up and Running with PyTorch: Introduction<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Lesson 1: PyTorch for the Impatient <\/span><br \/><span style=\"vertical-align: inherit\">1.1 What Is PyTorch? <\/span><br \/><span style=\"vertical-align: inherit\">1.2 The PyTorch Layer Cake <\/span><br \/><span style=\"vertical-align: inherit\">1.3 The Deep Learning Software Trilemma <\/span><br \/><span style=\"vertical-align: inherit\">1.4 What Are Tensors, Really? <\/span><br \/><span style=\"vertical-align: inherit\">1.5 Tensors in PyTorch <\/span><br \/><span style=\"vertical-align: inherit\">1.6 Introduction to Computational Graphs <\/span><br \/><span style=\"vertical-align: inherit\">1.7 Backpropagation Is Just the Chain Rule <\/span><br \/><span style=\"vertical-align: inherit\">1.8 Effortless Backpropagation with torch.autograd <\/span><br \/><span style=\"vertical-align: inherit\">1.9 PyTorch\u2019s Device Abstraction (ie, GPUs) <\/span><br \/><span style=\"vertical-align: inherit\">1.10 Working with Devices <\/span><br \/><span style=\"vertical-align: inherit\">1.11 Components of a Learning Algorithm <\/span><br \/><span style=\"vertical-align: inherit\">1.12 Introduction to Gradient Descent <\/span><br \/><span style=\"vertical-align: inherit\">1.13 Getting to Stochastic Gradient Descent (SGD) <\/span><br \/><span style=\"vertical-align: inherit\">1.14 Comparing Gradient Descent and SGD <\/span><br \/><span style=\"vertical-align: inherit\">1.15 Linear Regression with PyTorch <\/span><br \/><span style=\"vertical-align: inherit\">1.16 Perceptrons and Neurons <\/span><br \/><span style=\"vertical-align: inherit\">1.17 Layers and Activations with torch.nn <\/span><br \/><span style=\"vertical-align: inherit\">1.18 Multi-layer Feedforward Neural Networks (MLP)<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Summary <\/span><br \/><span style=\"vertical-align: inherit\">Up and Running with PyTorch: Summary<\/span><\/li>\n<\/ul>\n<\/div>\n<h3 dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Course images<\/span><\/h3>\n<p dir=\"ltr\" style=\"text-align: left\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-984842 size-full\" src=\"https:\/\/downloadly.ir\/wp-content\/uploads\/2025\/05\/Up-and-Running-with-PyTorch.png\" alt=\"Up and Running with PyTorch\" width=\"1243\" height=\"434\"><\/p>\n<h3 dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Sample course video<\/span><\/h3>\n<div style=\"width: 640px;\" class=\"wp-video\"><span class=\"mejs-offscreen\">Video Player<\/span><\/p>\n<div id=\"mep_0\" class=\"mejs-container mejs-container-keyboard-inactive wp-video-shortcode mejs-video\" tabindex=\"0\" role=\"application\" aria-label=\"Video Player\" style=\"width: 640px; height: 360px; min-width: 217px;\">\n<div class=\"mejs-inner\">\n<div class=\"mejs-mediaelement\"><mediaelementwrapper id=\"video-165257-1\"><video class=\"wp-video-shortcode\" id=\"video-165257-1_html5\" width=\"640\" height=\"360\" preload=\"metadata\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Up_and_Running_with_PyTorch_Downloadly.ir.mp4?_=1\" style=\"width: 640px; height: 360px;\"><source type=\"video\/mp4\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Up_and_Running_with_PyTorch_Downloadly.ir.mp4?_=1\"><a href=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Up_and_Running_with_PyTorch_Downloadly.ir.mp4?nocache=1786137945204\">https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/Up_and_Running_with_PyTorch_Downloadly.ir.mp4<\/a><\/video><\/mediaelementwrapper><\/div>\n<div class=\"mejs-layers\">\n<div class=\"mejs-poster mejs-layer\" style=\"display: none; width: 100%; height: 100%;\"><\/div>\n<div class=\"mejs-overlay mejs-layer\" style=\"display: none; width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-loading\"><span class=\"mejs-overlay-loading-bg-img\"><\/span><\/div>\n<\/div>\n<div class=\"mejs-overlay mejs-layer\" style=\"display: none; width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-error\"><\/div>\n<\/div>\n<div class=\"mejs-overlay mejs-layer mejs-overlay-play\" style=\"width: 100%; height: 100%;\">\n<div class=\"mejs-overlay-button\" role=\"button\" tabindex=\"0\" aria-label=\"Play\" aria-pressed=\"false\"><\/div>\n<\/div>\n<\/div>\n<div class=\"mejs-controls\">\n<div class=\"mejs-button mejs-playpause-button mejs-play\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Play\" aria-label=\"Play\" tabindex=\"0\"><\/button><\/div>\n<div class=\"mejs-time mejs-currenttime-container\" role=\"timer\" aria-live=\"off\"><span class=\"mejs-currenttime\">00:00<\/span><\/div>\n<div class=\"mejs-time-rail\"><span class=\"mejs-time-total mejs-time-slider\" role=\"slider\" tabindex=\"0\" aria-label=\"Time Slider\" aria-valuemin=\"0\" aria-valuemax=\"0\" aria-valuenow=\"0\" aria-valuetext=\"00:00\"><span class=\"mejs-time-buffering\" style=\"display: none;\"><\/span><span class=\"mejs-time-loaded\"><\/span><span class=\"mejs-time-current\"><\/span><span class=\"mejs-time-hovered no-hover\"><\/span><span class=\"mejs-time-handle\"><span class=\"mejs-time-handle-content\"><\/span><\/span><span class=\"mejs-time-float\"><span class=\"mejs-time-float-current\">00:00<\/span><span class=\"mejs-time-float-corner\"><\/span><\/span><\/span><\/div>\n<div class=\"mejs-time mejs-duration-container\"><span class=\"mejs-duration\">00:00<\/span><\/div>\n<div class=\"mejs-button mejs-volume-button mejs-mute\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Mute\" aria-label=\"Mute\" tabindex=\"0\"><\/button><a href=\"javascript:void(0);\" class=\"mejs-volume-slider\" aria-label=\"Volume Slider\" aria-valuemin=\"0\" aria-valuemax=\"100\" role=\"slider\" aria-orientation=\"vertical\"><span class=\"mejs-offscreen\">Use Up\/Down Arrow keys to increase or decrease volume.<\/span><\/p>\n<div class=\"mejs-volume-total\">\n<div class=\"mejs-volume-current\" style=\"bottom: 0px; height: 100%;\"><\/div>\n<div class=\"mejs-volume-handle\" style=\"bottom: 100%; margin-bottom: -3px;\"><\/div>\n<\/div>\n<p><\/a><\/div>\n<div class=\"mejs-button mejs-fullscreen-button\"><button type=\"button\" aria-controls=\"mep_0\" title=\"Fullscreen\" aria-label=\"Fullscreen\" tabindex=\"0\"><\/button><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div dir=\"ltr\" style=\"text-align: left\">\n<h3><span style=\"vertical-align: inherit\">Installation Guide<\/span><\/h3>\n<p><span style=\"vertical-align: inherit\">After Extract, view with your favorite player.<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">Subtitles: None<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">Quality: 720p<\/span><\/p>\n<\/div>\n<h3 dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Download link<\/span><\/h3>\n<p dir=\"ltr\" style=\"text-align: left\"><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Oreilly_Up_and_Running_with_PyTorch_2025-3_Downloadly.ir.rar?nocache=1786137943\"><span style=\"vertical-align: inherit\">Download file \u2013 680 MB<\/span><\/a><\/p>\n<p dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">File(s) password: www.downloadly.ir<\/span><\/p>\n<h3 dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">File size<\/span><\/h3>\n<p dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">680 MB<\/span><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Description Up and Running with PyTorch course. This course teaches the basics of working with PyTorch, one of the powerful deep learning frameworks. It begins <\/p>\n","protected":false},"author":1,"template":"","dgi_category":[10458],"dgi_tag":[87946,87947,87948,87949,87950,74183],"class_list":["post-10400","digital_item","type-digital_item","status-publish","has-post-thumbnail","hentry","dgi_category-video-tutorials","dgi_tag-course-up-and-running-with-pytorch","dgi_tag-download-course-up-and-running-with-pytorch","dgi_tag-download-up-and-running-with-pytorch","dgi_tag-free-download-up-and-running-with-pytorch","dgi_tag-free-up-and-running-with-pytorch","dgi_tag-jonathan-dinu"],"_links":{"self":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item\/10400","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item"}],"about":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/types\/digital_item"}],"author":[{"embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":0,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item\/10400\/revisions"}],"wp:attachment":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/media?parent=10400"}],"wp:term":[{"taxonomy":"dgi_category","embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/dgi_category?post=10400"},{"taxonomy":"dgi_tag","embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/dgi_tag?post=10400"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}