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Resources

Take our 85+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!

Author: Souradip Pal

Understanding the Math Behind Gradient Boosting: A Step-by-Step Guide
Artificial Intelligence  Data Science  Latest  Machine Learning

Understanding the Math Behind Gradient Boosting: A Step-by-Step Guide

Souradip Pal
1 like
October 1, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re trying to predict housing prices based on various factors, such as location, size, or the number of bedrooms. The challenge? …

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Gradient Boosting Explained: Turning Mistakes Into Precision
Artificial Intelligence  Data Science  Latest  Machine Learning

Gradient Boosting Explained: Turning Mistakes Into Precision

Souradip Pal
0 like
September 30, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re a teacher, and you’re trying to predict the future salaries of your students based on two factors: their IQ and …

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Regularization in Machine Learning: Mastering Ridge, Lasso, and Elastic Net
Artificial Intelligence  Data Science  Latest  Machine Learning

Regularization in Machine Learning: Mastering Ridge, Lasso, and Elastic Net

Souradip Pal
1 like
September 19, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. The story of regularization starts with a simple yet crucial problem that haunts many machine learning models: overfitting. Picture this — you’ve …

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Outlier Detection for Data Science: Practical Techniques and Tools Explained
Data Analysis  Data Science  Latest  Machine Learning

Outlier Detection for Data Science: Practical Techniques and Tools Explained

Souradip Pal
2 likes
September 16, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re looking at a large dataset filled with customer purchases. Suddenly, you notice one purchase that’s 10 times the average value! …

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The Balancing Act of Machine Learning: Bias-Variance Tradeoff
Artificial Intelligence  Data Science  Latest  Machine Learning

The Balancing Act of Machine Learning: Bias-Variance Tradeoff

Souradip Pal
1 like
September 16, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Once upon a time, in the world of machine learning, data scientists faced a constant challenge: finding the balance between a model …

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Building & Deploying a FastAPI Video Description App: From Code to Cloud with GPT, Docker and Azure
Latest  Machine Learning

Building & Deploying a FastAPI Video Description App: From Code to Cloud with GPT, Docker and Azure

Souradip Pal
1 like
September 11, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Ever wanted to turn a video into a text description without manually watching and writing down the details? Well, you’re in luck! …

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Building a Conversational Medical Form with GPT-4, Langchain, and SQLite
Latest  Machine Learning

Building a Conversational Medical Form with GPT-4, Langchain, and SQLite

Souradip Pal
1 like
September 11, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re sitting in a doctor’s office. Instead of filling out a cold, static medical form filled with dozens of boxes to …

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Handling Mixed Variables in Feature Engineering: A Practical Guide with Code
Artificial Intelligence  Data Science  Latest  Machine Learning

Handling Mixed Variables in Feature Engineering: A Practical Guide with Code

Souradip Pal
1 like
September 8, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. A girl looking at a screen containing mixed variables. Source: Image generated by Dall-E Imagine you’re working on a brand-new data project, …

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A Beginner’s Guide to Converting Numerical Data to Categorical: Binning and Binarization
Artificial Intelligence  Data Science  Latest  Machine Learning

A Beginner’s Guide to Converting Numerical Data to Categorical: Binning and Binarization

Souradip Pal
0 like
September 8, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine sifting through rows of data in a spreadsheet packed with numbers that look impressive at first glance. But when you try …

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Mathematical Transformations in Feature Engineering: Log, Reciprocal, and Power Transforms Explained with Visualization
Data Science  Latest  Machine Learning

Mathematical Transformations in Feature Engineering: Log, Reciprocal, and Power Transforms Explained with Visualization

Souradip Pal
1 like
September 4, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re preparing to bake a cake, but some ingredients are piled high, and others barely fill the spoon. Without smoothing out …

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Simplifying Data Preprocessing with ColumnTransformer in Python: A Step-by-Step Guide
Data Analysis  Data Science  Latest  Machine Learning

Simplifying Data Preprocessing with ColumnTransformer in Python: A Step-by-Step Guide

Souradip Pal
0 like
September 3, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re in a busy kitchen, trying to prepare a gourmet meal. You’ve got various ingredients laid out, each needing a different …

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Encoding Categorical Data: A Step-by-Step Guide
Data Analysis  Data Science  Latest  Machine Learning

Encoding Categorical Data: A Step-by-Step Guide

Souradip Pal
1 like
September 2, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Imagine you’re baking a cake, but instead of sugar, flour, and eggs, you have words like “vanilla,” “chocolate,” and “strawberry” on your …

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The Curse of Dimensionality: Why More Isn’t Always Better in Machine Learning
Artificial Intelligence  Latest  Machine Learning

The Curse of Dimensionality: Why More Isn’t Always Better in Machine Learning

Souradip Pal
0 like
August 27, 2024

Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. In the world of machine learning, you’re often knee-deep in datasets. These datasets could be anything — a collection of housing prices, …

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Building Your First Machine Learning Model with Linear Regression Using Ordinary Least Square
Artificial Intelligence  Latest  Machine Learning

Building Your First Machine Learning Model with Linear Regression Using Ordinary Least Square

Souradip Pal
1 like
August 25, 2024

Author(s): Souradip Pal Originally published on Towards AI. Let’s deep dive into the math and code it up from scratch This member-only story is on us. Upgrade to access all of Medium. Suppose you’re on the hunt for a new apartment in …

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Why scikit-learn isn’t the Best for Visualizing Decision Trees: Meet dtreeviz
Artificial Intelligence  Data Visualization  Latest  Machine Learning

Why scikit-learn isn’t the Best for Visualizing Decision Trees: Meet dtreeviz

Souradip Pal
1 like
August 23, 2024

Author(s): Souradip Pal Originally published on Towards AI. Fall in Love with Decision Trees with dtreeviz’s Visualization This member-only story is on us. Upgrade to access all of Medium. Decision Trees, also known as CART (Classification and Regression Trees), are undoubtedly one …

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`; } else { console.error('Element with id="subscribe" not found within the page with class "home".'); } } }); // Remove duplicate text from articles /* Backup: 09/11/24 function removeDuplicateText() { const elements = document.querySelectorAll('h1, h2, h3, h4, h5, strong'); // Select the desired elements const seenTexts = new Set(); // A set to keep track of seen texts const tagCounters = {}; // Object to track instances of each tag elements.forEach(el => { const tagName = el.tagName.toLowerCase(); // Get the tag name (e.g., 'h1', 'h2', etc.) // Initialize a counter for each tag if not already done if (!tagCounters[tagName]) { tagCounters[tagName] = 0; } // Only process the first 10 elements of each tag type if (tagCounters[tagName] >= 2) { return; // Skip if the number of elements exceeds 10 } const text = el.textContent.trim(); // Get the text content const words = text.split(/\s+/); // Split the text into words if (words.length >= 4) { // Ensure at least 4 words const significantPart = words.slice(0, 5).join(' '); // Get first 5 words for matching // Check if the text (not the tag) has been seen before if (seenTexts.has(significantPart)) { // console.log('Duplicate found, removing:', el); // Log duplicate el.remove(); // Remove duplicate element } else { seenTexts.add(significantPart); // Add the text to the set } } tagCounters[tagName]++; // Increment the counter for this tag }); } removeDuplicateText(); */ // Remove duplicate text from articles function removeDuplicateText() { const elements = document.querySelectorAll('h1, h2, h3, h4, h5, strong'); // Select the desired elements const seenTexts = new Set(); // A set to keep track of seen texts const tagCounters = {}; // Object to track instances of each tag // List of classes to be excluded const excludedClasses = ['medium-author', 'post-widget-title']; elements.forEach(el => { // Skip elements with any of the excluded classes if (excludedClasses.some(cls => el.classList.contains(cls))) { return; // Skip this element if it has any of the excluded classes } const tagName = el.tagName.toLowerCase(); // Get the tag name (e.g., 'h1', 'h2', etc.) // Initialize a counter for each tag if not already done if (!tagCounters[tagName]) { tagCounters[tagName] = 0; } // Only process the first 10 elements of each tag type if (tagCounters[tagName] >= 10) { return; // Skip if the number of elements exceeds 10 } const text = el.textContent.trim(); // Get the text content const words = text.split(/\s+/); // Split the text into words if (words.length >= 4) { // Ensure at least 4 words const significantPart = words.slice(0, 5).join(' '); // Get first 5 words for matching // Check if the text (not the tag) has been seen before if (seenTexts.has(significantPart)) { // console.log('Duplicate found, removing:', el); // Log duplicate el.remove(); // Remove duplicate element } else { seenTexts.add(significantPart); // Add the text to the set } } tagCounters[tagName]++; // Increment the counter for this tag }); } removeDuplicateText(); //Remove unnecessary text in blog excerpts document.querySelectorAll('.blog p').forEach(function(paragraph) { // Replace the unwanted text pattern for each paragraph paragraph.innerHTML = paragraph.innerHTML .replace(/Author\(s\): [\w\s]+ Originally published on Towards AI\.?/g, '') // Removes 'Author(s): XYZ Originally published on Towards AI' .replace(/This member-only story is on us\. Upgrade to access all of Medium\./g, ''); // Removes 'This member-only story...' }); //Load ionic icons and cache them if ('localStorage' in window && window['localStorage'] !== null) { const cssLink = 'https://code.ionicframework.com/ionicons/2.0.1/css/ionicons.min.css'; const storedCss = localStorage.getItem('ionicons'); if (storedCss) { loadCSS(storedCss); } else { fetch(cssLink).then(response => response.text()).then(css => { localStorage.setItem('ionicons', css); loadCSS(css); }); } } function loadCSS(css) { const style = document.createElement('style'); style.innerHTML = css; document.head.appendChild(style); } //Remove elements from imported content automatically function removeStrongFromHeadings() { const elements = document.querySelectorAll('h1, h2, h3, h4, h5, h6, span'); elements.forEach(el => { const strongTags = el.querySelectorAll('strong'); strongTags.forEach(strongTag => { while (strongTag.firstChild) { strongTag.parentNode.insertBefore(strongTag.firstChild, strongTag); } strongTag.remove(); }); }); } removeStrongFromHeadings(); "use strict"; window.onload = () => { /* //This is an object for each category of subjects and in that there are kewords and link to the keywods let keywordsAndLinks = { //you can add more categories and define their keywords and add a link ds: { keywords: [ //you can add more keywords here they are detected and replaced with achor tag automatically 'data science', 'Data science', 'Data Science', 'data Science', 'DATA SCIENCE', ], //we will replace the linktext with the keyword later on in the code //you can easily change links for each category here //(include class="ml-link" and linktext) link: 'linktext', }, ml: { keywords: [ //Add more keywords 'machine learning', 'Machine learning', 'Machine Learning', 'machine Learning', 'MACHINE LEARNING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ai: { keywords: [ 'artificial intelligence', 'Artificial intelligence', 'Artificial Intelligence', 'artificial Intelligence', 'ARTIFICIAL INTELLIGENCE', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, nl: { keywords: [ 'NLP', 'nlp', 'natural language processing', 'Natural Language Processing', 'NATURAL LANGUAGE PROCESSING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, des: { keywords: [ 'data engineering services', 'Data Engineering Services', 'DATA ENGINEERING SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, td: { keywords: [ 'training data', 'Training Data', 'training Data', 'TRAINING DATA', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ias: { keywords: [ 'image annotation services', 'Image annotation services', 'image Annotation services', 'image annotation Services', 'Image Annotation Services', 'IMAGE ANNOTATION SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, l: { keywords: [ 'labeling', 'labelling', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, pbp: { keywords: [ 'previous blog posts', 'previous blog post', 'latest', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, mlc: { keywords: [ 'machine learning course', 'machine learning class', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, }; //Articles to skip let articleIdsToSkip = ['post-2651', 'post-3414', 'post-3540']; //keyword with its related achortag is recieved here along with article id function searchAndReplace(keyword, anchorTag, articleId) { //selects the h3 h4 and p tags that are inside of the article let content = document.querySelector(`#${articleId} .entry-content`); //replaces the "linktext" in achor tag with the keyword that will be searched and replaced let newLink = anchorTag.replace('linktext', keyword); //regular expression to search keyword var re = new RegExp('(' + keyword + ')', 'g'); //this replaces the keywords in h3 h4 and p tags content with achor tag content.innerHTML = content.innerHTML.replace(re, newLink); } function articleFilter(keyword, anchorTag) { //gets all the articles var articles = document.querySelectorAll('article'); //if its zero or less then there are no articles if (articles.length > 0) { for (let x = 0; x < articles.length; x++) { //articles to skip is an array in which there are ids of articles which should not get effected //if the current article's id is also in that array then do not call search and replace with its data if (!articleIdsToSkip.includes(articles[x].id)) { //search and replace is called on articles which should get effected searchAndReplace(keyword, anchorTag, articles[x].id, key); } else { console.log( `Cannot replace the keywords in article with id ${articles[x].id}` ); } } } else { console.log('No articles found.'); } } let key; //not part of script, added for (key in keywordsAndLinks) { //key is the object in keywords and links object i.e ds, ml, ai for (let i = 0; i < keywordsAndLinks[key].keywords.length; i++) { //keywordsAndLinks[key].keywords is the array of keywords for key (ds, ml, ai) //keywordsAndLinks[key].keywords[i] is the keyword and keywordsAndLinks[key].link is the link //keyword and link is sent to searchreplace where it is then replaced using regular expression and replace function articleFilter( keywordsAndLinks[key].keywords[i], keywordsAndLinks[key].link ); } } function cleanLinks() { // (making smal functions is for DRY) this function gets the links and only keeps the first 2 and from the rest removes the anchor tag and replaces it with its text function removeLinks(links) { if (links.length > 1) { for (let i = 2; i < links.length; i++) { links[i].outerHTML = links[i].textContent; } } } //arrays which will contain all the achor tags found with the class (ds-link, ml-link, ailink) in each article inserted using search and replace let dslinks; let mllinks; let ailinks; let nllinks; let deslinks; let tdlinks; let iaslinks; let llinks; let pbplinks; let mlclinks; const content = document.querySelectorAll('article'); //all articles content.forEach((c) => { //to skip the articles with specific ids if (!articleIdsToSkip.includes(c.id)) { //getting all the anchor tags in each article one by one dslinks = document.querySelectorAll(`#${c.id} .entry-content a.ds-link`); mllinks = document.querySelectorAll(`#${c.id} .entry-content a.ml-link`); ailinks = document.querySelectorAll(`#${c.id} .entry-content a.ai-link`); nllinks = document.querySelectorAll(`#${c.id} .entry-content a.ntrl-link`); deslinks = document.querySelectorAll(`#${c.id} .entry-content a.des-link`); tdlinks = document.querySelectorAll(`#${c.id} .entry-content a.td-link`); iaslinks = document.querySelectorAll(`#${c.id} .entry-content a.ias-link`); mlclinks = document.querySelectorAll(`#${c.id} .entry-content a.mlc-link`); llinks = document.querySelectorAll(`#${c.id} .entry-content a.l-link`); pbplinks = document.querySelectorAll(`#${c.id} .entry-content a.pbp-link`); //sending the anchor tags list of each article one by one to remove extra anchor tags removeLinks(dslinks); removeLinks(mllinks); removeLinks(ailinks); removeLinks(nllinks); removeLinks(deslinks); removeLinks(tdlinks); removeLinks(iaslinks); removeLinks(mlclinks); removeLinks(llinks); removeLinks(pbplinks); } }); } //To remove extra achor tags of each category (ds, ml, ai) and only have 2 of each category per article cleanLinks(); */ //Recommended Articles var ctaLinks = [ /* ' ' + '

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',*/ ]; var replaceText = { '': '', '': '', '
': '
' + ctaLinks + '
', }; Object.keys(replaceText).forEach((txtorig) => { //txtorig is the key in replacetext object const txtnew = replaceText[txtorig]; //txtnew is the value of the key in replacetext object let entryFooter = document.querySelector('article .entry-footer'); if (document.querySelectorAll('.single-post').length > 0) { //console.log('Article found.'); const text = entryFooter.innerHTML; entryFooter.innerHTML = text.replace(txtorig, txtnew); } else { // console.log('Article not found.'); //removing comment 09/04/24 } }); var css = document.createElement('style'); css.type = 'text/css'; css.innerHTML = '.post-tags { display:none !important } .article-cta a { font-size: 18px; }'; document.body.appendChild(css); //Extra //This function adds some accessibility needs to the site. function addAlly() { // In this function JQuery is replaced with vanilla javascript functions const imgCont = document.querySelector('.uw-imgcont'); imgCont.setAttribute('aria-label', 'AI news, latest developments'); imgCont.title = 'AI news, latest developments'; imgCont.rel = 'noopener'; document.querySelector('.page-mobile-menu-logo a').title = 'Towards AI Home'; document.querySelector('a.social-link').rel = 'noopener'; document.querySelector('a.uw-text').rel = 'noopener'; document.querySelector('a.uw-w-branding').rel = 'noopener'; document.querySelector('.blog h2.heading').innerHTML = 'Publication'; const popupSearch = document.querySelector$('a.btn-open-popup-search'); popupSearch.setAttribute('role', 'button'); popupSearch.title = 'Search'; const searchClose = document.querySelector('a.popup-search-close'); searchClose.setAttribute('role', 'button'); searchClose.title = 'Close search page'; // document // .querySelector('a.btn-open-popup-search') // .setAttribute( // 'href', // 'https://medium.com/towards-artificial-intelligence/search' // ); } // Add external attributes to 302 sticky and editorial links function extLink() { // Sticky 302 links, this fuction opens the link we send to Medium on a new tab and adds a "noopener" rel to them var stickyLinks = document.querySelectorAll('.grid-item.sticky a'); for (var i = 0; i < stickyLinks.length; i++) { /* stickyLinks[i].setAttribute('target', '_blank'); stickyLinks[i].setAttribute('rel', 'noopener'); */ } // Editorial 302 links, same here var editLinks = document.querySelectorAll( '.grid-item.category-editorial a' ); for (var i = 0; i < editLinks.length; i++) { editLinks[i].setAttribute('target', '_blank'); editLinks[i].setAttribute('rel', 'noopener'); } } // Add current year to copyright notices document.getElementById( 'js-current-year' ).textContent = new Date().getFullYear(); // Call functions after page load extLink(); //addAlly(); setTimeout(function() { //addAlly(); //ideally we should only need to run it once ↑ }, 5000); }; function closeCookieDialog (){ document.getElementById("cookie-consent").style.display = "none"; return false; } setTimeout ( function () { closeCookieDialog(); }, 15000); console.log(`%c 🚀🚀🚀 ███ █████ ███████ █████████ ███████████ █████████████ ███████████████ ███████ ███████ ███████ ┌───────────────────────────────────────────────────────────────────┐ │ │ │ Towards AI is looking for contributors! │ │ Join us in creating awesome AI content. │ │ Let's build the future of AI together → │ │ https://towardsai.net/contribute │ │ │ └───────────────────────────────────────────────────────────────────┘ `, `background: ; color: #00adff; font-size: large`); //Remove latest category across site document.querySelectorAll('a[rel="category tag"]').forEach(function(el) { if (el.textContent.trim() === 'Latest') { // Remove the two consecutive spaces (  ) if (el.nextSibling && el.nextSibling.nodeValue.includes('\u00A0\u00A0')) { el.nextSibling.nodeValue = ''; // Remove the spaces } el.style.display = 'none'; // Hide the element } }); // Add cross-domain measurement, anonymize IPs 'use strict'; //var ga = gtag; ga('config', 'G-9D3HKKFV1Q', 'auto', { /*'allowLinker': true,*/ 'anonymize_ip': true/*, 'linker': { 'domains': [ 'medium.com/towards-artificial-intelligence', 'datasets.towardsai.net', 'rss.towardsai.net', 'feed.towardsai.net', 'contribute.towardsai.net', 'members.towardsai.net', 'pub.towardsai.net', 'news.towardsai.net' ] } */ }); ga('send', 'pageview'); -->