Videos de machine learning
Videos etiquetados con "machine learning"
machine learning 66 videos
Large Language Models (LLMs) Explained From Scratch (Complete Beginner's Guide) | TAB 47
#largelanguagemodels #llmfullcourse #llmfromscratch Want to understand Large Language Models (LLMs) without complicated math? In this video, you'll learn what a Large Language Model is, how LLMs work, and why models like ChatGPT, Claude, Gemini, and DeepSeek are transforming AI. This complete LLM tutorial for beginners explains every fundamental concept step by step, including language models, AI models, next-word prediction, pre-training, fine-tuning, parameters, weights, biases, datasets, compute, and the difference between Small Language Models (SLMs) and Large Language Models (LLMs). Whether you're preparing for AI Engineering, Machine Learning, Generative AI, Prompt Engineering, or simply want to understand how modern AI works, this video builds a strong foundation from scratch. Click to start your Career in GenAI - MICROSOFT GenAI Course - https://bit.ly/4oxRGaF only Rs 299/ Join our WhatsApp Channel to get the latest updates, learning resources, job trends, and exclusive content : https://whatsapp.com/channel/0029Vb7v6JA3LdQdLhL9rQ2i Below are the concepts covered in this video : 00:26 – Introduction & What You'll Learn 01:54 – What Is a Large Language Model (LLM)? 03:50 – What Is Language? (Vocabulary, Grammar & Meaning) 05:31 – Programming Languages vs Human Languages 06:45 – What Is an AI Model? 10:33 – Models as Mathematical Approximations 12:13 – What Is a Language Model? 12:48 – Next Word Prediction Explained 15:10 – Why Is It Called a Large Language Model? 17:27 – Datasets, Parameters & Compute 18:43 – Weights, Biases & Parameters 19:22 – Small Language Models (SLMs) vs Large Language Models (LLMs) 21:48 – LLM Recap: Language + Model + Large 22:24 – Sequence Prediction Example 26:44 – Pre-training vs Fine-tuning 28:57 – Discriminative vs Generative Models 29:41 – What Is a Generative Model? #generativeai #deeplearning #llm #softwareengineer #webdevelopment #localllm #aiagents #aitools #llmtutorial
Large Language Models (LLMs) Explained | No Coding Required | Vishwa sir | Tab 47
#llm #machinelearning #softwareengineering Want to understand how ChatGPT, Claude, Gemini, and other modern AI models actually work? Join this LIVE LLM Masterclass where we'll break down Large Language Models (LLMs) in the simplest possible way—no coding or programming experience required. Whether you're a student, working professional, AI enthusiast, or someone planning to build AI applications in the future, this live session will help you understand the core concepts behind today's most powerful AI systems. 🔗 Ready to build a career in AI? Join upGrad's Artificial Intelligence Courses and start learning from industry experts: https://bit.ly/4uRBTFU What you'll learn: What are Large Language Models (LLMs)? How ChatGPT and modern AI models work Tokens, embeddings, transformers, and attention explained Training vs inference Prompt engineering fundamentals Open-source vs closed-source LLMs Real-world applications of LLMs How LLMs power AI Agents, RAG, copilots, and automation The best roadmap to start learning Generative AI
🤯 How AI Creates Images From Pure Noise! (Stable Diffusion Explained)
🤯 How can AI create breathtaking images from just a few words? In this video, you'll discover the fascinating technology behind Stable Diffusion, DALL·E, Midjourney, and modern AI image generators. Learn step by step how Diffusion Models work: ✅ What is a Diffusion Model? ✅ Forward Process (Adding Noise) ✅ Reverse Process (Denoising) ✅ U-Net Neural Networks ✅ Latent Space & VAE ✅ CLIP and Text Prompts ✅ Stable Diffusion Architecture ✅ How AI Turns Text Into Images Whether you're interested in Artificial Intelligence, Machine Learning, Generative AI, or Digital Art, this video will help you understand one of the most revolutionary technologies of our time. 🔥 Don't forget to Like, Subscribe, and turn on Notifications for more AI, Machine Learning, and Technology content. #StableDiffusion #ArtificialIntelligence #GenerativeAI #MachineLearning #AIImages #StableDiffusion #DiffusionModels #AI #ArtificialIntelligence #GenerativeAI #MachineLearning #DeepLearning #AIArt #Midjourney #Dalle #TextToImage #NeuralNetworks #ComputerVision #FutureTech #TechExplained
What is an LLM?
An LLM is a model trained on massive amounts of text that learns how words relate to each other. This lesson covers how text becomes tokens, how the model generates a response one token at a time, and why the transformer architecture is what makes modern LLMs so effective. 🖊️ Learning objectives: - What tokens are and why models use them - How auto-regressive next-token prediction works - What the transformer brings to the picture Every token requires a full pass of calculations across billions of parameters. Multiply that by thousands of users sending requests at once and you start to see why inference speed becomes a hard engineering problem. For more resources, you may check out our blog here, where you will find information on: - What is AI inference? Meaning, benefits and how it works - Inference speed or throughput? With RDUs, you don't have to choose #AI #LLM #Tokens #Transformers #SambaNova
How to Choose the Best AI Image Generator (Midjourney vs DALL-E vs Stable Diffusion) (2026)
In this video: How to Choose the Best AI Image Generator (Midjourney vs DALL-E vs Stable Diffusion) (2026) Subscribe and hit the bell for new videos every week! 🔗 TOOLS & RESOURCES: • Claude AI (free): https://claude.ai • ChatGPT: https://chat.openai.com • Canva (free — join link): https://www.canva.com/join/myv-gzr-ptz • Notion (free): https://notion.so • Zapier (free tier): https://zapier.com • NordVPN (67% off): https://go.nordvpn.net/aff_c?offer_id=15&aff_id=823d06043aa7fa9cfa5d7c3185cc204b99c104c7412d135e41dcb31207afe3b7 • SafetyWing Insurance: https://safetywing.com/?referenceID=26525115&utm_source=26525115&utm_medium=Ambassador • Hostinger (web hosting): https://www.hostinger.com/it?REFERRALCODE=KZXALF199EZ9 📥 FREE DOWNLOAD — AI Tools Cheat Sheet 2026: https://scalabletools.gumroad.com/l/oruyf 🚀 Want AI to run your entire business? Try S.C.A.L.A.: https://get-scala.com/?utm_source=youtube&utm_medium=aitoollab&utm_campaign=video 📧 Sponsorships & collabs: sponsor@get-scala.com ━━━━━━━━━━━━━━━━━━━━━ 🔔 Subscribe for daily AI tool reviews! 👍 Like this video if it helped you! ━━━━━━━━━━━━━━━━━━━━━ #AITools #AI #Productivity #AI2026 #TechReview #productivity #tutorial #2026
How to Generate AI Images: GANs, Stable Diffusion & Visual Language Models Explained in 8 Minutes.
How does AI create images that look real—even when the people, places, or scenes never existed? In this video, Luka Anicin explores the evolution of AI image generation, from Generative Adversarial Networks (GANs) to Diffusion Models like Stable Diffusion, DALL·E, and Midjourney, and finally to Visual Language Models (VLMs) that can both generate and understand images. You'll learn how GANs sparked the first wave of realistic AI-generated images, why diffusion models became the dominant approach for modern image generation, and how Visual Language Models are pushing AI beyond image creation into image understanding and multimodal reasoning. Topics covered: • What GANs (Generative Adversarial Networks) are and how they work • Why ThisPersonDoesNotExist became a breakthrough AI demonstration • How Diffusion Models generate images from noise • Stable Diffusion, DALL·E, and Midjourney explained • What Visual Language Models (VLMs) are • How AI combines image understanding and language generation • The strengths and limitations of GANs, Diffusion Models, and VLMs • The future of multimodal AI systems Whether you're studying Generative AI, Machine Learning, Computer Vision, or AI Engineering, this video will help you understand the technologies powering today's most advanced image-generation systems. @Saras_AI_Institute
Creé un coach de sentadillas con IA en 5 minutos | Visión computacional explicada
¿Y si tu cámara pudiera ayudarte con los ejercicios? En este video te muestro cómo creé un coach de sentadillas con visión computacional que cuenta tus repeticiones en tiempo real. Sin código complicado — solo la lógica, las tecnologías y cómo funciona detrás de cámaras. 📌 Lo que verás en este video: 00:00 - Introducción: ¿Y si tu cámara pudiera...? 00:15 - Demo en vivo del coach funcionando 00:30 - Cómo la computadora ve tu cuerpo (YOLOv8) 01:38 - La matemática del ángulo de rodilla 02:25 - Los 3 estados (arriba, bajando, abajo) 03:28 - Arquitectura: cámara → cerebro → voz → orquestador 04:19 - Cierre y próximos proyectos 💻 Código y documentación completa: https://github .com/PipetoBlack/coachSentadilla ────────────────────────────── 🔔 Suscríbete para no perderte los próximos laboratorios 📸 Instagram: @pipetolab ────────────────────────────── #VisionComputacional #Python #YOLO #OpenCV #InteligenciaArtificial #MachineLearning #DeepLearning #ComputerVision #PipetoLab #AprendizajeAutomático #IA #TutorialPython #PoseEstimation #Automacion
The Math Behind Deepfakes (GANs Explained)
Discover the math behind deepfakes and how Generative Adversarial Networks (GANs) changed AI forever. Before 2014, teaching a machine to create highly realistic data from scratch involved incredibly slow and complex probabilistic calculations. That all changed when Ian Goodfellow and his team introduced a completely new paradigm. By pitting two neural networks against each other in a continuous Minimax game, they bypassed the heavy calculus and unlocked the modern era of generative AI. In this video, we break down the exact mechanics of GANs. You will learn how the Generator acts as a counterfeiter trying to create perfect fakes, while the Discriminator acts as the police trying to catch them. We also dive into the training loop, the significance of the Jensen-Shannon divergence, and the mathematical proof that guarantees these models can perfectly mimic reality. 00:00 - The dense math of early generative models 00:58 - Re-framing generation as an adversarial game 02:27 - The Counterfeiter and the Police analogy 03:11 - The Minimax game and training loop steps 04:24 - Visualizing the push and pull of data distribution 05:58 - Proving the perfect fake mathematically 06:40 - The Jensen-Shannon divergence explained 07:31 - Why GANs matter for modern AI and deepfakes 🔗 Stay Connected 👉 Subscribe on YouTube: https://www.youtube.com/@insightforge_9 👉 Read the Blog (AI, Chatbots & Automation): https://insightforge-ai.blogspot.com/ 👉 Connect on LinkedIn: https://www.linkedin.com/in/mohit-rathod-7991241b5/ 👉 Join the Newsletter: https://www.linkedin.com/newsletters/7330620395449937920/ 👉 Follow on Instagram: https://www.instagram.com/insightforge.ai/ #GenerativeAI #MachineLearning #Deepfakes
No AI Job Apocalypse? New Study Says Automation Hasn't Replaced Workers At Scale Yet | N18G
A new study suggests there is currently no clear evidence that artificial intelligence has triggered widespread job losses, despite growing concerns about automation replacing human workers. Researchers say AI's impact on employment is more nuanced, with many jobs evolving rather than disappearing entirely. As businesses increasingly adopt AI technologies, experts believe the future of work will involve changing job roles, new skill requirements, and human-AI collaboration instead of a large-scale employment crisis. Watch the latest insights into AI, automation, the job market, and the future of work. #AI #ArtificialIntelligence #Automation #Jobs #FutureOfWork #TechNews #AIJobs #Employment #BreakingNews #Technology #JobMarket #LatestNews #Innovation #Workforce #newsupdate n18oc_world CNN-News18 is your trusted source for breaking news, updates, and in-depth analysis from around the world. CNN-News18 is dedicated to bringing you the latest news, trends, and insights, helping you stay informed and up-to-date. Subscribe Now and join our community of informed and engaged viewers. 24X7 LIVE TV: https://www.youtube.com/watch?v=rfDx1HMvXbQ Follow us on Google: news18.co/cn18g Follow CNN News18 on X: https://x.com/CNNnews18 Follow CNN News18 on Instagram: https://www.instagram.com/cnnnews18/ Follow CNN News18 on Facebook: facebook.com/cnnnews18 #GetCloserToTheNews with latest headlines on politics, sports and entertainment on news18.com News18 Mobile App - https://onelink.to/desc-youtube
Neural Networks Explained in 10 Minutes
Neural Networks are the foundation of modern Artificial Intelligence—and they power many of the AI tools you use every day, including ChatGPT, Claude, Gemini, Copilot, and more. But what exactly is a neural network, and how does it actually work? In this video, you’ll get a simple, non-technical explanation of neural networks in just 10 minutes. No advanced mathematics, no coding, and no computer science degree required. We’ll break down the core concepts behind how AI learns, recognizes patterns, and generates intelligent responses. Whether you’re a manager, business professional, student, entrepreneur, or simply curious about AI, understanding neural networks is one of the most valuable skills you can build in today’s AI-driven world. 📌 In This Video: ✅ What is a Neural Network? ✅ Why Neural Networks Are Important in AI ✅ How Neural Networks Learn Patterns ✅ Input Layer, Hidden Layers & Output Layer Explained ✅ How AI Makes Predictions and Decisions ✅ The Connection Between Neural Networks and Deep Learning ✅ How ChatGPT, Claude, Gemini, and Copilot Use Neural Networks ✅ Real-World Examples of Neural Networks in Business 🎯 Who Should Watch? ✔ Business Professionals ✔ Managers & Team Leaders ✔ Supply Chain Professionals ✔ Operations Leaders ✔ Students & Career Switchers ✔ AI Beginners ✔ Entrepreneurs ✔ Anyone Curious About Artificial Intelligence Understanding neural networks helps you understand the technology behind today’s most powerful AI systems. Once you grasp this concept, topics like Machine Learning, Deep Learning, Large Language Models (LLMs), ChatGPT, and Generative AI become much easier to understand. 🚀 AI is changing every industry. The professionals who understand how it works will be better positioned to leverage it, manage it, and create value with it. 👇 What AI topic would you like explained next? Let me know in the comments. 🔔 Subscribe for more videos on: • Artificial Intelligence • Neural Networks • Machine Learning • Deep Learning • Large Language Models (LLMs) • Generative AI • AI for Business • Supply Chain & Operations • Career Growth • Future of Work
Las 3 habilidades que la IA NUNCA podrá robar | Protege tu futuro ahora
¿Cómo afectará la inteligencia artificial a tu trabajo? Analizamos el informe del Foro Económico Mundial sobre el futuro laboral. La inteligencia artificial está cambiando el mercado laboral a una velocidad sin precedentes. En este análisis, examinamos los datos reales detrás de la automatización para entender qué significa esto para tu carrera profesional en los próximos años. Si te preocupa la estabilidad de tu empleo, este contenido es para ti. Basándonos en el informe publicado por el Foro Económico Mundial en 2023, exploramos la proyección de que 85 millones de puestos de trabajo serán impactados por la inteligencia artificial en el corto plazo. Analizamos las consecuencias directas de esta tendencia global y cómo prepararse ante la inminente llegada de nuevas tecnologías al entorno corporativo. Entender el impacto de la inteligencia artificial es clave para mantenerse relevante. Suscríbete para recibir análisis semanales sobre el futuro del trabajo y cuéntanos en los comentarios si crees que tu profesión está a salvo de estos cambios. ▶ Lo que aprenderás: ✅ Cómo usar la IA a tu favor desde hoy ✅ Las habilidades que NUNCA podrá reemplazar ✅ Cómo combinar tu experiencia con IA ✅ El hábito de 30 minutos que cambia todo ✅ Cómo construir tu red para el futuro ⏱️ Capítulos: 0:00 Introducción 0:40 El problema real 1:30 Aprende a usar la IA 2:30 Habilidades humanas 3:30 Sé el experto de tu área 4:30 Aprende continuamente 5:20 Construye tu red 6:10 El plan completo 7:00 Conclusión 🔔 Suscríbete a IA Sin Filtros #InteligenciaArtificial #IA #Trabajo #Empleo #FuturoDelTrabajo #2027 #ChatGPT #Automatización
LLM 101: From Basics to Advanced in Minutes
LLM 101: From Basics to Advanced in Minutes What is an LLM? How do Large Language Models work? How does ChatGPT generate human-like responses? In this video, we break down Large Language Models (LLMs) from basics to advanced concepts in a simple and practical way. If you’ve heard terms like LLM, Large Language Models, ChatGPT, Generative AI, Transformers, Tokens, Embeddings, RAG, Fine-Tuning, Prompt Engineering, and AI Agents, this video will help you understand how they all fit together. Large Language Models are the foundation of modern Artificial Intelligence and power tools such as ChatGPT, Claude, Gemini, Copilot, Perplexity, and many enterprise AI applications. What You’ll Learn ✅ What is a Large Language Model (LLM)? ✅ How Large Language Models Work ✅ How ChatGPT Works ✅ What Are Tokens in LLMs? ✅ Transformer Architecture Explained ✅ Neural Networks Explained ✅ How LLMs Are Trained ✅ What Are Embeddings? ✅ Fine-Tuning vs Prompt Engineering ✅ What is Retrieval-Augmented Generation (RAG)? ✅ AI Agents Explained ✅ Real-World Applications of Large Language Models Large Language Models Explained A Large Language Model (LLM) is an Artificial Intelligence model trained on massive amounts of text data to understand and generate human language. Large Language Models use Machine Learning, Deep Learning, Transformer Architecture, and Neural Networks to predict the next word in a sequence and generate intelligent responses. Modern LLMs power: * ChatGPT * Claude * Gemini * Microsoft Copilot * Enterprise AI Assistants * AI Agents * Customer Support Bots * AI Search Engines * Business Automation Systems Key Concepts Covered * Large Language Models (LLMs) * Artificial Intelligence * Machine Learning * Deep Learning * Transformer Models * Neural Networks * Tokens * Embeddings * Context Windows * Prompt Engineering * Fine-Tuning * RAG Architecture * AI Agents * Generative AI * Natural Language Processing (NLP) Real-World Applications of LLMs Learn how Large Language Models are transforming: ✔ Business Operations ✔ Supply Chain Management ✔ Customer Support ✔ Content Creation ✔ Research and Analysis ✔ Marketing and Sales ✔ Software Development ✔ Knowledge Management ✔ Enterprise Productivity Who Should Watch? * AI Beginners * Working Professionals * Managers * Business Leaders * Students * Data Analysts * Supply Chain Professionals * Operations Managers * Entrepreneurs * Technology Enthusiasts