Python to GenAI Course — Week 6 | DL Foundations - Part 2

Join us live as we cover three full lessons in one session — from understanding which neural network to pick, to building and running real models. Here's what we'll go through together: 🧭 P2.3.5 — Types of Neural Networks • The 4 types: ANN, CNN, RNN, LSTM — what each one is for • The full decision table — given your data and task, which network do you use? 🧠 P2.3.6 — ANN in Practice • ANN vs Linear Regression — why not just stick with regression? • Feature Scaling — why it matters and how to do it • Full 4-phase workflow: Split → Train → Evaluate → Inference • Build a house price predictor with Keras 👁️ P2.3.7 — CNN — Three Real Examples • How CNN actually works: Convolution, Pooling, Flatten, Pipelines • Classification vs Object Detection — same backbone, different head • Example 1: MNIST digit classifier from scratch (Google Colab) • Example 2: Cats vs Dogs with VGG16 Transfer Learning (Google Colab) • Example 3: YOLO Object Detection running locally — no GPU needed Bring your questions — we answer live. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📂 Part of the GenAI Foundation Course ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📁 GitHub: https://github.com/MaighaInc/pycore/tree/main/Course-GenAIFoundation/P2_LegacyToGenAI/P2.3_DL_Foundations 💬 Discord: https://discord.com/invite/V35dKcApS6 ────────────────────────────── 🔔 Subscribe so you don't miss the next session 👍 Like if you're joining live 💬 Drop your questions in chat — we read every one ────────────────────────────── See you live! 🚀 📅 Date: March 21 ⏰ Time: 7:00 PM IST