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Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-François Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
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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!

Category: Machine Learning

Exploring Activation Functions, Loss Functions, and Optimization Algorithms
Latest  Machine Learning

Exploring Activation Functions, Loss Functions, and Optimization Algorithms

Ali
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September 5, 2024

Author(s): Ali Originally published on Towards AI. A Beginner-friendly overview This member-only story is on us. Upgrade to access all of Medium. Neural Network -source (author) When building Deep Learning models, activation functions, loss functions, and optimizing algorithms are crucial components that …

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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
0 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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Compare & Understand: Designing Chatbot Applications With a UI Mindset — Part 2
Latest  Machine Learning

Compare & Understand: Designing Chatbot Applications With a UI Mindset — Part 2

Sanjay Krishna Anbalagan
0 like
September 4, 2024

Author(s): Sanjay Krishna Anbalagan Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. In Part 1, we explored how designing chatbot applications can mirror the mental model of traditional UI-based frontend applications. As we …

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Compare & Understand: Designing Chatbot Applications With a UI Mindset — Part 1
Latest  Machine Learning

Compare & Understand: Designing Chatbot Applications With a UI Mindset — Part 1

Sanjay Krishna Anbalagan
0 like
September 4, 2024

Author(s): Sanjay Krishna Anbalagan Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. As Generative AI evolves, chatbots are becoming a cornerstone of modern applications. Traditionally, front-end applications rely on UI-based interactions — users …

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I created a Character Counter using ChatGPT & YouTube
Latest  Machine Learning

I created a Character Counter using ChatGPT & YouTube

Nizamuddin Siddiqui
1 like
September 4, 2024

Author(s): Nizamuddin Siddiqui Originally published on Towards AI. You can too, in minutes This member-only story is on us. Upgrade to access all of Medium. Taken from my Character Counter First of all, I am not a programmer but I can write …

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Optimizing Machine Learning Models: A Deep Dive into Hyperparameter Tuning Techniques
Data Science  Latest  Machine Learning

Optimizing Machine Learning Models: A Deep Dive into Hyperparameter Tuning Techniques

MD TAHSEEN EQUBAL
1 like
September 4, 2024

Author(s): MD TAHSEEN EQUBAL Originally published on Towards AI. Grid Search, Random Search and Bayesian Optimization Introduction to Hyperparameters Hyperparameters are the external parameters of a machine learning model that are not learned from the data. Instead, they are set before the …

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Revisiting Chunking in the RAG Pipeline
Latest  Machine Learning

Revisiting Chunking in the RAG Pipeline

Florian June
0 like
September 4, 2024

Author(s): Florian June Originally published on Towards AI. Unveiling the Cutting-Edge Advances in Chunking This member-only story is on us. Upgrade to access all of Medium. Chunking involves dividing a long text or document into smaller, logically coherent segments or “chunks.” Each …

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AI and Wedding Photography, A Match Made in Heaven
Latest  Machine Learning

AI and Wedding Photography, A Match Made in Heaven

Diop Papa Makhtar
0 like
September 4, 2024

Author(s): Diop Papa Makhtar Originally published on Towards AI. AI and Wedding Photography, A Match Made in Heaven picture of a wedding with a robot holding a camera, generated by Microsoft copilot As an entrepreneur with a passion for technology and a …

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Forget Houses, Smart Investors Are Buying Data Centers. Here’s Why.
Data Science  Latest  Machine Learning

Forget Houses, Smart Investors Are Buying Data Centers. Here’s Why.

KayDee
1 like
September 4, 2024

Author(s): KayDee Originally published on Towards AI. How data centers became hot real estate investments. This member-only story is on us. Upgrade to access all of Medium. Photo by Shubham Dhage on Unsplash Not a Medium Member? Read this Article for Free …

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Building a Simple Linear Regression Model on Azure to Predict Car Prices
Cloud Computing  Data Science  Latest  Machine Learning

Building a Simple Linear Regression Model on Azure to Predict Car Prices

Julius Nyerere Nyambok
1 like
September 4, 2024

Author(s): Julius Nyerere Nyambok Originally published on Towards AI. Hello there, gentle reader!I am Nyerere Julius, an aspiring machine learning engineer and cloud solution specialist, deeply intrigued by the vast possibilities that AI and ML offer. In this project, I’ll guide you …

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How Does AI Work? Create a Neural Network from Scratch
Artificial Intelligence  Latest  Machine Learning

How Does AI Work? Create a Neural Network from Scratch

Sean Jude Lyons
0 like
September 4, 2024

Author(s): Sean Jude Lyons Originally published on Towards AI. By the end of this article, you’ll be able to build your own model and Machine Learning library to make predictions. Let's begin by writing a simple function and discussing it: def parabola_function(x): …

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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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KNNs & K-Means: The Superior Alternative to Clustering & Classification.
Artificial Intelligence  Latest  Machine Learning

KNNs & K-Means: The Superior Alternative to Clustering & Classification.

Surya Maddula
1 like
September 3, 2024

Author(s): Surya Maddula Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Let’s discuss two popular ML algorithms, KNNs and K-Means. Stick around; I’ll make this densely packed. P.S. I’m trying out a new …

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TAI #115: LLM Adoption Taking Off? OpenAI API Use Up 2x in 5 Weeks, LLama at 350m Downloads.
Artificial Intelligence  Latest  Machine Learning

TAI #115: LLM Adoption Taking Off? OpenAI API Use Up 2x in 5 Weeks, LLama at 350m Downloads.

Towards AI Editorial Team
1 like
September 3, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, we saw several new LLMs released, including an upgrade to Cohere’s Command R and new Qwen2 models. Outside of LLMs, we also …

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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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`; } 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'); -->