CNN Convolutions Explained Clearly — Filters, Padding, Stride & Feature Maps скачать в хорошем качестве

CNN Convolutions Explained Clearly — Filters, Padding, Stride & Feature Maps

This video is part of my Deep Learning Foundations series, where we build intuition first and then move toward real-world implementation. 👉 If you’re new to deep learning, I strongly recommend starting with the earlier intuition videos in this playlist: How a Deep Learning Algorithm Works Weights & Parameters Activation Functions Loss Functions 📚 Deep Learning Foundations Playlist:    • What is Artificial Intelligence, Machine L...   In this video, we break down convolutions in CNNs step by step — visually and intuitively — so the core ideas finally click. How convolutional filters slide over an image How feature maps are created What padding and stride really do How output shapes change across CNN layers By the end, you’ll clearly understand how CNNs extract local patterns, build hierarchical features, and transform images into meaningful representations — without getting lost in heavy math. In the upcoming videos, we’ll continue this journey by: Exploring pooling layers in more depth 🎓 This content is adapted from my Udemy course: Deep Learning Mastery: Build Your AI Foundation 👉 https://www.udemy.com/course/deep-lea...