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Data Visualization 29.06.2025.ipynb
Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb

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, '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" + '

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Data Visualization 29.06.2025.ipynb
Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb
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, '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('^' + ".*" + '

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Data Visualization 29.06.2025.ipynb
Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb
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, '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('^' + ".*" + '

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Data Visualization 29.06.2025.ipynb
Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb
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, '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" + '

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Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb
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, '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('^' + ".*" + '

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Data Visualization 29.06.2025.ipynb
Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb
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, '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('^' + ".*" + '

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Data Visualization 29.06.2025.ipynb
Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb
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, '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); }
})();
})();

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.ipynb_checkpoints
.ipynb_checkpoints
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Data Visualization 29.06.2025.ipynb
Data Visualization 29.06.2025.ipynb
Data Visualization Practise.ipynb
Data Visualization Practise.ipynb
Decision Tree Classification.ipynb
Decision Tree Classification.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
Diabetes Prediction Logistic Regression, Random Forest, XGBoost.ipynb
KNearest Neighbors Classification.ipynb
KNearest Neighbors Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Logistic Regression Fine Tunning Classification.ipynb
Model 1 Linear Regression.ipynb
Model 1 Linear Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 2 Polynomial Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 3 Multilinear Regression.ipynb
Model 4 Logistic regression.ipynb
Model 4 Logistic regression.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 5 Logistic Regression COVID.ipynb
Model 6 Lasso Regression (1).ipynb
Model 6 Lasso Regression (1).ipynb
Model 7 Ridge Regression.ipynb
Model 7 Ridge Regression.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1 - XGBoost, Life Expectancy Project.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
Project 1, Life Expectancy - Multiple Linear Regression.ipynb
ROC Curve Classification.ipynb
ROC Curve Classification.ipynb
Random Forest Classification.ipynb
Random Forest Classification.ipynb
Random Forest Tree Classification Problem.ipynb
Random Forest Tree Classification Problem.ipynb
SVM Model Classification.ipynb
SVM Model Classification.ipynb
Solutions Math for Data Science (1).ipynb
Solutions Math for Data Science (1).ipynb
XGBOOST for Mushroom dataset Classification.ipynb
XGBOOST for Mushroom dataset Classification.ipynb
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