Python to GenAI Course — Week 5 | DL Foundations - Part 1

🔥 LIVE RECAP: In 30 minutes, we climb the entire mountain of deep learning fundamentals. From "Why do we need deep learning?" all the way to "How does a network actually learn?" We've covered THE FOUR PILLARS this week. Now let's lock it in together live. 📌 What We're Recapping: → P2.3.1 — Why Deep Learning? (Rule-Based AI hits its limits. Neural nets don't.) → P2.3.2 — The Neuron (The atom of ML. Inputs, weights, bias, activation. Pure Python.) → P2.3.3 — Neuron to Network (Stack neurons into layers. Forward pass. Network shape decisions.) → P2.3.4 — How Networks Learn (Loss. Backpropagation. Gradient Descent. The learning loop.) 💡 Why Watch This Recap? You NOW understand what happens under the hood. No black boxes. When you see a Keras model or PyTorch network in the wild, you'll think: "Oh, that's just what we built from scratch, but the framework automated it." 🔔 Subscribe and enable notifications — new lesson every week. 👍 Like if this week clicked for you. 💬 Drop your toughest question in the comments — we read them all. See you live! 🚀 📅 Date: March 14th ⏰ Time: 8:00 PM IST