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CPSC 370: Deep Learning

School: Chapman University
Term: Fall 2019
Website:Class homepage

Topics

  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2

First day checklist

  • Read the prerequisites notebook
  • Run python ready_for_class.py
  • Complete the test questions in here. These are due on the first day

To view the notebooks as slides run

jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources

Blogs

lilianweng.github.io
colah.github.io
Gradient

Other Courses

Machine Learning

Deep Learning

Reinforcement Learning

About

Course material from when I taught deep learning at Chapman University

Resources

Readme
Activity

Stars

7 stars

Watchers

2 watching

Forks

5 forks
Report repository

Releases

Packages

Used by

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
CPSC 370: Deep Learning
School: Chapman University
Term: Fall 2019
Website:Class homepage
Topics
  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2
First day checklist
  •  Read the prerequisites notebook
  •  Run python ready_for_class.py
  •  Complete the test questions in here. These are due on the first day
To view the notebooks as slides run
jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources
Blogs
lilianweng.github.io
colah.github.io
Gradient
Other Courses
Machine Learning
Deep Learning
Reinforcement Learning
About
Course material from when I taught deep learning at Chapman University
Resources
Readme
Activity
Stars
7 stars
Watchers
2 watching
Forks
5 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
CPSC 370: Deep Learning
School: Chapman University
Term: Fall 2019
Website:Class homepage
Topics
  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2
First day checklist
  •  Read the prerequisites notebook
  •  Run python ready_for_class.py
  •  Complete the test questions in here. These are due on the first day
To view the notebooks as slides run
jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources
Blogs
lilianweng.github.io
colah.github.io
Gradient
Other Courses
Machine Learning
Deep Learning
Reinforcement Learning
About
Course material from when I taught deep learning at Chapman University
Resources
Readme
Activity
Stars
7 stars
Watchers
2 watching
Forks
5 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
CPSC 370: Deep Learning
School: Chapman University
Term: Fall 2019
Website:Class homepage
Topics
  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2
First day checklist
  •  Read the prerequisites notebook
  •  Run python ready_for_class.py
  •  Complete the test questions in here. These are due on the first day
To view the notebooks as slides run
jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources
Blogs
lilianweng.github.io
colah.github.io
Gradient
Other Courses
Machine Learning
Deep Learning
Reinforcement Learning
About
Course material from when I taught deep learning at Chapman University
Resources
Readme
Activity
Stars
7 stars
Watchers
2 watching
Forks
5 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
CPSC 370: Deep Learning
School: Chapman University
Term: Fall 2019
Website:Class homepage
Topics
  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2
First day checklist
  •  Read the prerequisites notebook
  •  Run python ready_for_class.py
  •  Complete the test questions in here. These are due on the first day
To view the notebooks as slides run
jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources
Blogs
lilianweng.github.io
colah.github.io
Gradient
Other Courses
Machine Learning
Deep Learning
Reinforcement Learning
About
Course material from when I taught deep learning at Chapman University
Resources
Readme
Activity
Stars
7 stars
Watchers
2 watching
Forks
5 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
CPSC 370: Deep Learning
School: Chapman University
Term: Fall 2019
Website:Class homepage
Topics
  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2
First day checklist
  •  Read the prerequisites notebook
  •  Run python ready_for_class.py
  •  Complete the test questions in here. These are due on the first day
To view the notebooks as slides run
jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources
Blogs
lilianweng.github.io
colah.github.io
Gradient
Other Courses
Machine Learning
Deep Learning
Reinforcement Learning
About
Course material from when I taught deep learning at Chapman University
Resources
Readme
Activity
Stars
7 stars
Watchers
2 watching
Forks
5 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
CPSC 370: Deep Learning
School: Chapman University
Term: Fall 2019
Website:Class homepage
Topics
  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2
First day checklist
  •  Read the prerequisites notebook
  •  Run python ready_for_class.py
  •  Complete the test questions in here. These are due on the first day
To view the notebooks as slides run
jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources
Blogs
lilianweng.github.io
colah.github.io
Gradient
Other Courses
Machine Learning
Deep Learning
Reinforcement Learning
About
Course material from when I taught deep learning at Chapman University
Resources
Readme
Activity
Stars
7 stars
Watchers
2 watching
Forks
5 forks
Report repository
Releases
Packages
Used by
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
CPSC 370: Deep Learning
School: Chapman University
Term: Fall 2019
Website:Class homepage
Topics
  1. Prerequisites
  2. Linear Regression to Multi Layer Perceptrons
  3. Universal Approximation Theorem
  4. Training Neural Networks
  5. Convolutional Neural Networks
  6. Convolutional Neural Network Applications
  7. Autoencoders
  8. Recurrent Neural Networks
  9. Attention
  10. Generative Adversarial Networks
  11. Neuroscience and Deep Learning
  12. Reinforcement Learning Part 1
  13. Reinforcement Learning Part 2
First day checklist
  •  Read the prerequisites notebook
  •  Run python ready_for_class.py
  •  Complete the test questions in here. These are due on the first day
To view the notebooks as slides run
jupyter nbconvert Notebooks/01\ Introduction.ipynb --to slides --post serve

Resources
Blogs
lilianweng.github.io
colah.github.io
Gradient
Other Courses
Machine Learning
Deep Learning
Reinforcement Learning
About
Course material from when I taught deep learning at Chapman University
Resources
Readme
Activity
Stars
7 stars
Watchers
2 watching
Forks
5 forks
Report repository
Releases
Packages
Used by
Contributors
Languages