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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

[AI] Neurosymbolic AI — A Microthesis
Latest  Machine Learning

[AI] Neurosymbolic AI — A Microthesis

Shashwat Gupta
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October 26, 2024

Author(s): Shashwat Gupta Originally published on Towards AI. Neurosymbolic AI presents potential solutions to the existing challenges of LLMs by integrating neural networks with logic and reasoning. This may be advantageous for industries such as healthcare, finance, and cybersecurity. Employing Neurosymbolic AI, …

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CCoE: Approach to Mastering Multiple Domains with LLMs
Artificial Intelligence  Data Science  Latest  Machine Learning

CCoE: Approach to Mastering Multiple Domains with LLMs

Manpreet Singh
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October 26, 2024

Author(s): Manpreet Singh Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Source: https://aisera.com/blog AI is changing quickly, and big language models (LLMs) like GPT-4 are making waves because they understand and create text …

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Unmasking the Machine: How AI Can Detect an AI Essay or Article?
Artificial Intelligence  Latest  Machine Learning

Unmasking the Machine: How AI Can Detect an AI Essay or Article?

Veritas AI
1 like
October 26, 2024

Author(s): Veritas AI Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Generated by Dall-E AI The line between original human-generated text and artificially intelligent text has gotten blurrier with each passing day in …

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Building Trustworthy AI: Interpretability in Vision and Linguistic Models
Artificial Intelligence  Computer Vision  Data Science  Latest  Machine Learning

Building Trustworthy AI: Interpretability in Vision and Linguistic Models

Rohan Vij
0 like
October 26, 2024

Author(s): Rohan Vij Originally published on Towards AI. Building Trustworthy AI: Interpretability in Vision and Linguistic Models Photo by Arteum.ro on Unsplash | What thoughts lie behind that eye? The rise of large artificial intelligence (AI) models trained using self-supervised deep learning …

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Revolutionizing Document Processing: Hierarchy-Based Chunking with Accurate Data Extraction — Part-1
Latest  Machine Learning

Revolutionizing Document Processing: Hierarchy-Based Chunking with Accurate Data Extraction — Part-1

Sashidhar Reddy
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October 26, 2024

Author(s): Sashidhar Reddy Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Photo by Ignacio Pérez In today’s world of information overload, documents come in all forms — PDFs, Word files, PowerPoint presentations — …

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Building Confidence in LLM Evaluation: My Experience Testing DeepEval on an Open Dataset
Latest  Machine Learning

Building Confidence in LLM Evaluation: My Experience Testing DeepEval on an Open Dataset

Serj Smorodinsky
1 like
October 26, 2024

Author(s): Serj Smorodinsky Originally published on Towards AI. deepeval helped me uncover what is the real source of Beyonce’s depression Long Story Short If you’re looking to catch LLM hallucinations — output that introduces information not present in the input — you …

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The Transformer Architecture
Latest  Machine Learning

The Transformer Architecture

Derrick Mwiti
1 like
October 25, 2024

Author(s): Derrick Mwiti Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Photo by Samule Sun on Unsplash In 2017, Ashish Vaswani et al wrote a paper that would change the natural language processing …

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AI-Driven Decision Making: Comparing Markov Decision Process and Reinforcement Learning
Latest  Machine Learning

AI-Driven Decision Making: Comparing Markov Decision Process and Reinforcement Learning

Shenggang Li
1 like
October 25, 2024

Author(s): Shenggang Li Originally published on Towards AI. How Trump and Harris Could Use MDP and RL to Maximize Their Chances in the 2024 Election This member-only story is on us. Upgrade to access all of Medium. Photo by Chad Stembridge on …

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Llama Dive
Latest  Machine Learning

Llama Dive

Derrick Mwiti
2 likes
October 25, 2024

Author(s): Derrick Mwiti Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Photo by Gustavo Espíndola on Unsplash It’s no doubt that generative AI will change every industry. The current state of generative AI, …

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Data Query & Visualisation using LLM Agents from Scratch
Artificial Intelligence  Latest  Machine Learning

Data Query & Visualisation using LLM Agents from Scratch

Akash Modi
2 likes
October 25, 2024

Author(s): Akash Modi Originally published on Towards AI. Building a simple data analysis & plotting engine using LLaMa and LangChain Agentic Framework with Structured Data This member-only story is on us. Upgrade to access all of Medium. Image by author In this …

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GPTFX-the new era of machine learning in mental health care
Artificial Intelligence  Latest  Machine Learning

GPTFX-the new era of machine learning in mental health care

MSVPJ Sathvik
0 like
October 25, 2024

Author(s): MSVPJ Sathvik Originally published on Towards AI. Mental health has remained one of the most challenging aspects of modern healthcare. A lot of people among us suffer from mental health problems and are looking for support and timely diagnosis without being …

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Large Language Model Evaluation Metrics
Latest  Machine Learning

Large Language Model Evaluation Metrics

Derrick Mwiti
1 like
October 25, 2024

Author(s): Derrick Mwiti Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Photo by Possessed Photography on Unsplash The most common evaluating metrics for large language models are: PerplexityBLEUROUGEBERTScoreCOMETMETEORBLEURTGPTScorePRISMBARTScoreG-EvalHuman Evaluation Evaluating large language models(LLMs) …

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Speech-To-SQL Using OpenAI’s Whisper and Ollama (Llama3)
Latest  Machine Learning

Speech-To-SQL Using OpenAI’s Whisper and Ollama (Llama3)

Tapan Babbar
0 like
October 25, 2024

Author(s): Tapan Babbar Originally published on Towards AI. Source: 10points Gryffindor Richard Harris GIF by blue_elephant on Tenor I was rewatching the Harry Potter series and kept wondering: teachers and prefects were deducting points from houses left and right! But do they …

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Quantile Random Forests: Predicting Beyond the Mean
Latest  Machine Learning

Quantile Random Forests: Predicting Beyond the Mean

Sanjay Nandakumar
0 like
October 25, 2024

Author(s): Sanjay Nandakumar Originally published on Towards AI. Photo by Marcel Eberle on Unsplash “An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.” John Tukey Table of contents Introduction What …

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A Comprehensive Guide to Vector Stores in Generative AI
Latest  Machine Learning

A Comprehensive Guide to Vector Stores in Generative AI

Mdabdullahalhasib
1 like
October 25, 2024

Author(s): Mdabdullahalhasib Originally published on Towards AI. Understand the concept of Vector Store, Importance & Use Cases, Various Vector Store provides, and implementation with LangChain This member-only story is on us. Upgrade to access all of Medium. Source: Photo by Bozhin Karaivanov …

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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'); -->