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deep learning courses
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sdwalker62 committed Jun 18, 2024
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2 changes: 1 addition & 1 deletion frontend/src/lib/components/Courses/PageLink.svelte
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#widget-canvas {
display: flex;
align-items: center;
justify-content: center;
justify-content: space-between;
background: var(--background-10);
gap: 1.5rem;
padding: 1rem 1rem;
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4 changes: 4 additions & 0 deletions frontend/src/routes/courses/+page.svelte
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background: var(--gradient-1);
cursor: pointer;
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&::-webkit-scrollbar {
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.course-title {
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81 changes: 60 additions & 21 deletions frontend/src/routes/courses/deep_learning/+page.svelte
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<main>
<div id="main-background__container">
<h1>Deep Learning</h1>
<p> This is a course on Deep learning!</p>
<p>description coming soon</p>
<div id="main-course__grid">
<div class="course-list__container">
<h3>Introduction</h3>
<h3>Linear Classifiers and Gradient Descent</h3>
<PageLink
title="Introduction to Deep Learning"
description="This will introduce you to the fundamentals of Deep Learning. It covers loss functions, activation functions, network optimization, and more."
link="/courses/deep_learning/introduction"
title="Supervised Learning and Parametric Models"
description="Supervised Learning and Parametric Models"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/Supervised%20Learning%20and%20Parametric%20Models.md"
/>
<PageLink
title="Introduction to Deep Learning"
description="This will introduce you to the fundamentals of Deep Learning. It covers loss functions, activation functions, network optimization, and more."
link="/courses/deep_learning/introduction"
/>
</div>
<div class="course-list__container">
<h3>Introduction</h3>
title="Components of a Parametric Learning Algorithm"
description="Components of a Parametric Learning Algorithm"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/Components%20of%20A%20Parametric%20Learning%20Algorithm.md"
/>
<PageLink
title="Introduction to Deep Learning"
description="This will introduce you to the fundamentals of Deep Learning. It covers loss functions, activation functions, network optimization, and more."
link="/courses/deep_learning/introduction"
title="Performance Measure For A Classifier"
description="Performance Measure For A Classifier"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/Performance%20Measure%20For%20A%20Classifier.md"
/>
<PageLink
title="Linear Algebra View: Vector and Matrix Sizes"
description="Linear Algebra View: Vector and Matrix Sizes"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/Linear%20Algebra%20View:%20Vector%20and%20Matrix%20Sizes.md"
/>
<PageLink
title="How is Deep Learning Different? Hierarchical Compositionality"
description="How is Deep Learning Different? Hierarchical Compositionality"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/How%20is%20Deep%20Learning%20Different:%20HC.md"
/>
<PageLink
title="How is Deep Learning Different? End-to-End Learning"
description="How is Deep Learning Different? End-to-End Learning"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/How%20is%20Deep%20Learning%20Different:%20End-to-End.md"
/>
<PageLink
title="Gradient Descent"
description="Gradient Descent"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/Gradient%20Descent.md"
/>
<PageLink
title="How is Deep Learning Different? Distributed Representations"
description="How is Deep Learning Different? Distributed Representations"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/How%20is%20Deep%20Learning%20Different:%20DR.md"
/>
<PageLink
title="Deep Learning Book: Linear Algebra"
description="Deep Learning Book: Linear Algebra"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/DL_Book_Linear_Algebra.pdf"
/>
<PageLink
title="Deep Learning Book: Probability and Information Theory"
description="Deep Learning Book: Probability and Information Theory"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/DL_Book_Probability_And_Information_Theory.pdf"
/>
<PageLink
title="Deep Learning Book: Machine Learning Basics"
description="Deep Learning Book: Machine Learning Basics"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/DL_Book_Machine_Learning_Basics.pdf"
/>
<PageLink
title="Deep Learning"
description="Deep Learning"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/Deep_Learning.pdf"
/>
</div>
<div class="course-list__container">
<h3>Introduction</h3>
<PageLink
title="Introduction to Deep Learning"
description="This will introduce you to the fundamentals of Deep Learning. It covers loss functions, activation functions, network optimization, and more."
link="/courses/deep_learning/introduction"
title="The Bandwagon"
description="The Bandwagon"
link="https://athenalib.com/docs//var/www/athenalib.com/source/frontend/data/Machine%20Learning/Deep%20Learning/Novice/Module%201%20-%20Lesson%201:%20Linear%20Classifiers%20and%20Gradient%20Descent/The_Bandwagon.pdf"
/>
</div>
</div>
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