🧠 𝗔𝗜 𝘃𝘀 𝗠𝗟 𝘃𝘀 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 𝘃𝘀 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 – 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 𝗶𝗻 𝗢𝗻𝗲 𝗩𝗶𝘀𝘂𝗮𝗹! 🚀 If you're confused by all the buzzwords flying around — Artificial Intelligence, Machine Learning, Neural Networks, Deep Learning — you're not alone. Let’s break it down 👇 🔵 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗔𝗜) is the broadest umbrella — covering any technique that enables computers to mimic human intelligence. This includes planning, reasoning, language understanding, and decision-making. 🟡 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗠𝗟) is a subset of AI. It's all about teaching machines to learn from data without being explicitly programmed. Think algorithms like Decision Trees, K-Means, and SVM. 🟢 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 are a subset of ML, inspired by the human brain. These include architectures like Radial Basis Networks and RNNs, capable of identifying complex patterns. 🔴 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 is a subset of Neural Networks — using multiple layers to process data and extract intricate features. It's behind modern marvels like ChatGPT, image recognition, and autonomous vehicles. 📌 Whether you're just starting your AI journey or diving deeper into advanced models like Transformers and GANs, this visual helps frame where everything fits. 💡 𝗦𝗮𝘃𝗲 𝘁𝗵𝗶𝘀 𝗽𝗼𝘀𝘁 for your learning journey. 📢 𝗦𝗵𝗮𝗿𝗲 𝗶𝘁 with someone trying to understand the AI landscape. 💬 𝗖𝗼𝗺𝗺𝗲𝗻𝘁 𝗯𝗲𝗹𝗼𝘄 — where are you in this AI ecosystem? Are you learning ML, experimenting with Deep Learning, or just exploring? #artificialintelligence #datscience