Videos de deep learning

Videos etiquetados con "deep learning"

deep learning 36 videos

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11:06

Neural Network - How it Works

Neural Network - How it Works 📲 For More Content like this, be sure to Subscribe to our channel! ✅Thanks For Watching: Neural Network - How it Works Here at Thinking Machines, we aim to create top-quality videos about artificial intelligence, machine learning, tech documentaries, AI controversies, big tech developments, robotics, automation, future concepts, and the science shaping tomorrow—covering everything happening in the world of technology and AI. Our goal is to help you understand how AI is changing the world, uncover the stories behind major tech revolutions, and explore the ideas, companies, and breakthroughs building our future. Neural networks learn to recognize patterns by adjusting millions of mathematical connections instead of relying on manually programmed rules. The video explains how raw input data, such as image pixels, flows through layers of neurons that detect increasingly complex features before producing a final prediction. It breaks down key concepts like weights, biases, activation functions, and training in a simple, intuitive way, showing how each component contributes to the network's learning process. You'll also discover why neural networks have become the foundation of modern AI applications, from image recognition and translation to speech processing and self-driving cars. By the end, you'll understand that the power of neural networks comes not from magic or human-like thinking, but from countless simple mathematical operations working together to uncover meaningful patterns. 💻For Business Inquiries, Collaborations or Promotions, contact us at: odedschannel1@gmail.com #neuralnetworks Networks, #artificialintelligence Intelligence, #AI, #machinelearning Learning, Deep Learning, How Neural Networks Work, Neural Network Explained, AI Explained, #aivideo for Beginners, Deep Learning Tutorial, #artificialintelligencetechnology Neural Network, ANN, Weights and Biases, Activation Functions, ReLU, Sigmoid Function, Hidden Layers, Input Layer, Output Layer, Pattern Recognition, Image Recognition, Handwritten Digit Recognition, Computer Vision, AI Training, Backpropagation, Neural Network Training, Parameters, AI Models, Mathematics of AI, Modern AI, Generative AI, Large Language Models, Deep Learning Fundamentals, Data Science, Computer Science, AI Technology, AI Education, #aigenerated Concepts, How AI Learns, Pattern Detection, Predictive Models, Educational Technology, Future of AI, Thinking Machines, Tech Explained, AI Tutorial, Neural Network Basics, Machine Intelligenc

hace 4 días 35

3:59

Así funciona REALMENTE la Inteligencia Artificial (en 4 minutos)

Explicación sin tecnicismos de qué es la IA de verdad, machine learning, los 4 tipos de aprendizaje automático (supervisado, no supervisado, semi-supervisado, por refuerzo), redes neuronales y deep learning.

hace 5 días 20

9:21

What is a Neural Network? | Neural Network Explained for Beginners | @quicklearnerss

🧠 Neural Networks are the foundation of modern Artificial Intelligence, Machine Learning, and Deep Learning. In this beginner-friendly tutorial, you'll learn how Artificial Neural Networks (ANN) work using simple language, real-life examples, and easy-to-understand animations. Whether you're a Computer Science student, engineering student, AI enthusiast, or preparing for placements and interviews, this video will help you understand Neural Networks from scratch. 📌 In this video, you'll learn: ✔ What is a Neural Network? ✔ Why Neural Networks are important? ✔ Biological Neuron vs Artificial Neuron ✔ Structure of an Artificial Neural Network ✔ Input Layer, Hidden Layer & Output Layer ✔ Weights, Bias, and Activation Function ✔ Feed Forward Process ✔ Training a Neural Network ✔ Backpropagation (Basic Introduction) ✔ Real-life Applications of Neural Networks 🎯 This video is perfect for: • B.Tech / BCA / MCA Students • AI & Machine Learning Beginners • Deep Learning Beginners • Placement Preparation • University Exam Preparation • GATE Aspirants • Anyone curious about Artificial Intelligence ━━━━━━━━━━━━━━━━━━━━ 📚 Prerequisites: Basic understanding of mathematics is helpful but not required. ━━━━━━━━━━━━━━━━━━━━ 🔥 Related Videos: ▶ Artificial Intelligence Complete Playlist ▶ Machine Learning for Beginners ▶ Deep Learning Tutorial ▶ Perceptron Explained ▶ Activation Functions Explained ▶ Machine Learning Roadmap ━━━━━━━━━━━━━━━━━━━━ 💻 Technologies Discussed: Artificial Intelligence Machine Learning Deep Learning Artificial Neural Networks Perceptron Activation Functions Backpropagation ━━━━━━━━━━━━━━━━━━━━ 👍 If you found this video helpful: ✔ Like the video ✔ Share it with your friends ✔ Subscribe for more AI and Computer Science tutorials ✔ Turn on the notification bell 🔔 #NeuralNetwork #ArtificialIntelligence #MachineLearning #DeepLearning #AI #ANN #DataScience #ComputerScience #AIForBeginners #DeepLearningTutorial

hace 1 semana 415

3:22

The Perceptron: All of AI Is One Neuron

Try it yourself. The full written explainer and an interactive perceptron you can click are here: https://unrote.com/ai/the-perceptron/ The perceptron is a single artificial neuron, and it is the atom that every neural network is built from. In this from-scratch explainer we build one step by step: the inputs, the weights, the weighted sum, the bias, and the activation that makes it fire. Then we watch what one neuron can do, draw a straight line to separate data, meet the famous pattern it cannot solve (XOR), and see how stacking neurons into layers turns them into deep learning. What you will understand by the end: - What a neuron actually takes in, and why each input is a number - Weights: how much each piece of evidence counts - The weighted sum and the bias, in plain terms - Activation: the step function that outputs a one or a zero - A worked decision, start to finish - How a perceptron learns its weights - One straight line, and the hard limit of a single neuron - Why stacking neurons into layers gives you a neural network Understand it, don't memorize it.

hace 1 semana 4

8:24

¿La IA en medicina es real? Opus 4.8 revela el futuro del diagnóstico

17 segundos fue lo que tardó Opus 4.8 en analizar una resonancia magnética, revelando hallazgos que los expertos médicos tardarían horas en procesar. La inteligencia artificial ha prometido revolucionar la medicina por años, pero el reciente experimento con Opus 4.8 analizando una resonancia magnética marca un antes y un después. Este suceso no solo valida la capacidad diagnóstica de los modelos de IA avanzados, sino que plantea preguntas cruciales sobre el rol humano en la salud, la ética y la velocidad de los avances tecnológicos. Entenderás qué implica para tu futuro médico y cómo afectará la atención sanitaria global. 🤖 EN ESTE VÍDEO: ✅ Cómo Opus 4.8 procesó la resonancia magnética y qué anomalías detectó ✅ La precisión sorprendente de la IA frente al diagnóstico médico tradicional ✅ Implicaciones éticas y el debate sobre la autonomía de la IA en salud ✅ Qué significa este avance para el futuro de tu atención médica ✅ Por qué este modelo de Anthropic supera a otros en razonamiento contextual Este hito con Opus 4.8 redefine la frontera entre IA y medicina, abriendo un abanico de posibilidades y desafíos. ¿Estás listo para confiar tu salud a un algoritmo? Suscríbete a MYBESTIA para no perderte las últimas novedades y déjanos tu opinión: ¿Crees que la IA debería tener la última palabra en diagnósticos médicos? ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🔔 SUSCRÍBETE para no perderte ninguna noticia: https://youtube.com/@fjqg?sub_confirmation=1 📡 SÍGUEME EN TODAS LAS REDES: 🌐 Web & blog → https://mybestia.com ▶️ YouTube → https://youtube.com/@fjqg?sub_confirmation=1 📸 Instagram → https://www.instagram.com/quintinogiaia/ 🎵 TikTok → https://www.tiktok.com/@mybestia 💬 Telegram → https://t.me/franciscoquintinogarcia_bot 🦋 Bluesky → https://bsky.app/profile/mybestia.bsky.social 🐘 Mastodon → https://mastodon.social/@mybestia 💼 LinkedIn → https://www.linkedin.com/in/franciscoquintino/ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 📂 MÁS VÍDEOS DEL CANAL: 🤖 IA y Automatización → https://youtube.com/@fjqg/videos 🔐 Ciberseguridad & Hack → https://youtube.com/@fjqg/videos 📱 Tech y Gadgets → https://youtube.com/@fjqg/videos ⚙️ Desarrollo & Código → https://youtube.com/@fjqg/videos ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 📌 SOBRE MYBESTIA — Francis Quintino Soy Francis Quintino, creador de contenido tech desde Palma de Mallorca 🌴 Especializado en inteligencia artificial, automatización con IA, ciberseguridad, pentesting autónomo, creación de páginas web con IA, e integración de IA en empresas. Todo el contenido de mybestia.com se genera con pipelines de IA propios — sin relleno, sin clickbait, datos reales. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🤖 AVISO DE TRANSPARENCIA Este vídeo ha sido generado y/o asistido por inteligencia artificial (voz, imágenes, edición y parte del guion). Es contenido divulgativo de carácter informativo y puede contener imprecisiones: verifica siempre las fuentes originales antes de tomar decisiones. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🏷️ MYBESTIA, Opus 4.8, Anthropic, inteligencia artificial, IA, medicina, diagnóstico médico, resonancia magnética, MRI, salud digital, tecnología 2024, ciberseguridad, ética IA, futuro de la medicina, machine learning, deep learning, tech español, innovación, análisis de datos, salud #InteligenciaArtificial #IAenMedicina #Opus4_8 #DiagnosticoAI #SaludDigital #Tecnologia2024

hace 2 semanas 12

8:24

¿La IA en medicina es real? Opus 4.8 revela el futuro del diagnóstico

hace 2 semanas 11

48:18

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

hace 2 semanas 137

8:21

🤯 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

hace 2 semanas 15

3:15

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

hace 2 semanas 20

7:32

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

hace 2 semanas 21

5:04

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

hace 3 semanas 50

8:37

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

hace 3 semanas 125

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