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    iicght/README.md

    Hi, I’m Ivan 👋

    🎓 Economics student interested in data analytics, ML, finance, and automation. I like combining economics and programming to build useful analytical tools and find insights in data.

    🛠 Tech Stack

    Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics

    Including:

    Regression · Classification · Clustering · Gradient Boosting · Feature Engineering

    Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics

    Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots

    🚀 Interests

    • 📊 Data analysis and visualization
    • 🤖 Machine learning for business and finance
    • 💸 Investment and credit analysis
    • ⚙️ Automation, parsers, and trading-related tools
    • 🧾 Economics, taxation, and financial statements

    🎯 Focus

    Building practical projects that turn data into clear decisions.

    📫 Contact:

    Pinned Loading

    1. customer-segmentation-mlcustomer-segmentation-mlPublic

      Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

      Jupyter Notebook

    2. loan-default-predictionloan-default-predictionPublic

      Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

      Jupyter Notebook

    3. PortfolioTheoryPortfolioTheoryPublic

      Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица.

      Python

    4. belarus-vodka-time-seriesbelarus-vodka-time-seriesPublic

      Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

      Jupyter Notebook

    5. salary-regression-rlmssalary-regression-rlmsPublic

      RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

      Jupyter Notebook

    , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} 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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      iicght/README.md
      Hi, I’m Ivan 👋
      🎓 Economics student interested in data analytics, ML, finance, and automation.
I like combining economics and programming to build useful analytical tools and find insights in data.
      🛠 Tech Stack
      Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics
      Including:
      Regression · Classification · Clustering · Gradient Boosting · Feature Engineering
      Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics
      Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots
      🚀 Interests
      • 📊 Data analysis and visualization
      • 🤖 Machine learning for business and finance
      • 💸 Investment and credit analysis
      • ⚙️ Automation, parsers, and trading-related tools
      • 🧾 Economics, taxation, and financial statements
      🎯 Focus
      Building practical projects that turn data into clear decisions.
      📫 Contact:
      
Pinned
Loading
      1. customer-segmentation-mlcustomer-segmentation-mlPublic
        
Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

        Jupyter Notebook
      2. loan-default-predictionloan-default-predictionPublic
        
Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

        Jupyter Notebook
      3. PortfolioTheoryPortfolioTheoryPublic
        
Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица. 
        Python
      4. belarus-vodka-time-seriesbelarus-vodka-time-seriesPublic
        
Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

        Jupyter Notebook
      5. salary-regression-rlmssalary-regression-rlmsPublic
        
RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

        Jupyter Notebook
      
, '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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      1
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 · 2
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        iicght/README.md
        Hi, I’m Ivan 👋
        🎓 Economics student interested in data analytics, ML, finance, and automation.
I like combining economics and programming to build useful analytical tools and find insights in data.
        🛠 Tech Stack
        Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics
        Including:
        Regression · Classification · Clustering · Gradient Boosting · Feature Engineering
        Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics
        Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots
        🚀 Interests
        • 📊 Data analysis and visualization
        • 🤖 Machine learning for business and finance
        • 💸 Investment and credit analysis
        • ⚙️ Automation, parsers, and trading-related tools
        • 🧾 Economics, taxation, and financial statements
        🎯 Focus
        Building practical projects that turn data into clear decisions.
        📫 Contact:
        
Pinned
Loading
        1. customer-segmentation-mlcustomer-segmentation-mlPublic
          
Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

          Jupyter Notebook
        2. loan-default-predictionloan-default-predictionPublic
          
Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

          Jupyter Notebook
        3. PortfolioTheoryPortfolioTheoryPublic
          
Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица. 
          Python
        4. belarus-vodka-time-seriesbelarus-vodka-time-seriesPublic
          
Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

          Jupyter Notebook
        5. salary-regression-rlmssalary-regression-rlmsPublic
          
RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

          Jupyter Notebook
        
, '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
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        1
follower
 · 2
following

          
Block or report iicght

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          iicght/README.md
          Hi, I’m Ivan 👋
          🎓 Economics student interested in data analytics, ML, finance, and automation.
I like combining economics and programming to build useful analytical tools and find insights in data.
          🛠 Tech Stack
          Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics
          Including:
          Regression · Classification · Clustering · Gradient Boosting · Feature Engineering
          Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics
          Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots
          🚀 Interests
          • 📊 Data analysis and visualization
          • 🤖 Machine learning for business and finance
          • 💸 Investment and credit analysis
          • ⚙️ Automation, parsers, and trading-related tools
          • 🧾 Economics, taxation, and financial statements
          🎯 Focus
          Building practical projects that turn data into clear decisions.
          📫 Contact:
          
Pinned
Loading
          1. customer-segmentation-mlcustomer-segmentation-mlPublic
            
Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

            Jupyter Notebook
          2. loan-default-predictionloan-default-predictionPublic
            
Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

            Jupyter Notebook
          3. PortfolioTheoryPortfolioTheoryPublic
            
Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица. 
            Python
          4. belarus-vodka-time-seriesbelarus-vodka-time-seriesPublic
            
Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

            Jupyter Notebook
          5. salary-regression-rlmssalary-regression-rlmsPublic
            
RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

            Jupyter Notebook
          
, '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
          View iicght's full-sized avatar
          1
follower
 · 2
following

            
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            iicght/README.md
            Hi, I’m Ivan 👋
            🎓 Economics student interested in data analytics, ML, finance, and automation.
I like combining economics and programming to build useful analytical tools and find insights in data.
            🛠 Tech Stack
            Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics
            Including:
            Regression · Classification · Clustering · Gradient Boosting · Feature Engineering
            Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics
            Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots
            🚀 Interests
            • 📊 Data analysis and visualization
            • 🤖 Machine learning for business and finance
            • 💸 Investment and credit analysis
            • ⚙️ Automation, parsers, and trading-related tools
            • 🧾 Economics, taxation, and financial statements
            🎯 Focus
            Building practical projects that turn data into clear decisions.
            📫 Contact:
            
Pinned
Loading
            1. customer-segmentation-mlcustomer-segmentation-mlPublic
              
Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

              Jupyter Notebook
            2. loan-default-predictionloan-default-predictionPublic
              
Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

              Jupyter Notebook
            3. PortfolioTheoryPortfolioTheoryPublic
              
Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица. 
              Python
            4. belarus-vodka-time-seriesbelarus-vodka-time-seriesPublic
              
Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

              Jupyter Notebook
            5. salary-regression-rlmssalary-regression-rlmsPublic
              
RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

              Jupyter Notebook
            
, '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
            View iicght's full-sized avatar
            1
follower
 · 2
following

              
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              iicght/README.md
              Hi, I’m Ivan 👋
              🎓 Economics student interested in data analytics, ML, finance, and automation.
I like combining economics and programming to build useful analytical tools and find insights in data.
              🛠 Tech Stack
              Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics
              Including:
              Regression · Classification · Clustering · Gradient Boosting · Feature Engineering
              Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics
              Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots
              🚀 Interests
              • 📊 Data analysis and visualization
              • 🤖 Machine learning for business and finance
              • 💸 Investment and credit analysis
              • ⚙️ Automation, parsers, and trading-related tools
              • 🧾 Economics, taxation, and financial statements
              🎯 Focus
              Building practical projects that turn data into clear decisions.
              📫 Contact:
              
Pinned
Loading
              1. customer-segmentation-mlcustomer-segmentation-mlPublic
                
Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

                Jupyter Notebook
              2. loan-default-predictionloan-default-predictionPublic
                
Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

                Jupyter Notebook
              3. PortfolioTheoryPortfolioTheoryPublic
                
Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица. 
                Python
              4. belarus-vodka-time-seriesbelarus-vodka-time-seriesPublic
                
Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

                Jupyter Notebook
              5. salary-regression-rlmssalary-regression-rlmsPublic
                
RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

                Jupyter Notebook
              
, '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
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              1
follower
 · 2
following

                
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                iicght/README.md
                Hi, I’m Ivan 👋
                🎓 Economics student interested in data analytics, ML, finance, and automation.
I like combining economics and programming to build useful analytical tools and find insights in data.
                🛠 Tech Stack
                Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics
                Including:
                Regression · Classification · Clustering · Gradient Boosting · Feature Engineering
                Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics
                Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots
                🚀 Interests
                • 📊 Data analysis and visualization
                • 🤖 Machine learning for business and finance
                • 💸 Investment and credit analysis
                • ⚙️ Automation, parsers, and trading-related tools
                • 🧾 Economics, taxation, and financial statements
                🎯 Focus
                Building practical projects that turn data into clear decisions.
                📫 Contact:
                
Pinned
Loading
                1. customer-segmentation-mlcustomer-segmentation-mlPublic
                  
Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

                  Jupyter Notebook
                2. loan-default-predictionloan-default-predictionPublic
                  
Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

                  Jupyter Notebook
                3. PortfolioTheoryPortfolioTheoryPublic
                  
Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица. 
                  Python
                4. belarus-vodka-time-seriesbelarus-vodka-time-seriesPublic
                  
Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

                  Jupyter Notebook
                5. salary-regression-rlmssalary-regression-rlmsPublic
                  
RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

                  Jupyter Notebook
                
, '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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                  iicght/README.md
                  Hi, I’m Ivan 👋
                  🎓 Economics student interested in data analytics, ML, finance, and automation.
I like combining economics and programming to build useful analytical tools and find insights in data.
                  🛠 Tech Stack
                  Data & ML:Python · Pandas · NumPy · Scikit-learn · Matplotlib · Seaborn · Statistics
                  Including:
                  Regression · Classification · Clustering · Gradient Boosting · Feature Engineering
                  Finance & Economics:Financial Analysis · Credit Analysis · Investment Modeling · Taxation · Accounting Basics
                  Tools:SQL · MySQL · Jupyter Notebook · APIs · Telegram Bots
                  🚀 Interests
                  • 📊 Data analysis and visualization
                  • 🤖 Machine learning for business and finance
                  • 💸 Investment and credit analysis
                  • ⚙️ Automation, parsers, and trading-related tools
                  • 🧾 Economics, taxation, and financial statements
                  🎯 Focus
                  Building practical projects that turn data into clear decisions.
                  📫 Contact:
                  
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                  1. customer-segmentation-mlcustomer-segmentation-mlPublic
                    
Automated customer segmentation and behavioral analysis using Unsupervised Machine Learning to optimize marketing strategies.

                    Jupyter Notebook
                  2. loan-default-predictionloan-default-predictionPublic
                    
Machine learning models for credit scoring and bank loan default prediction using socio-demographic and financial data. Implemented detailed evaluation metrics logging to maximize bank profits.

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Реализация модели оптимизации инвестиционного портфеля на основе теории Марковица. 
                    Python
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Quarterly Belarus vodka sales forecasting with Holt-Winters, ARIMA, SARIMAX and Prophet using pandas, statsmodels and scikit-learn.

                    Jupyter Notebook
                  5. salary-regression-rlmssalary-regression-rlmsPublic
                    
RLMS salary analysis: EDA, preprocessing and comparison of OLS, Lasso, Ridge, SGD and ElasticNet with pandas, scikit-learn and statsmodels.

                    Jupyter Notebook