100 Days of Deep Learning - Pooling Layer in CNN | MaxPooling in Convolutional Neural Network

The pooling operation involves sliding a two-dimensional filter over each channel of the feature map and summarising the features lying within the region covered by the filter. Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes Code - https://colab.research.google.com/drive/1F4F6Q9O-hPvCDeOWcqMUa5BuBOvuOBWc?usp=sharing Demo - https://deeplizard.com/resource/pavq7noze3 ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 👍If you find this video helpful, consider giving it a thumbs up and subscribing for more educational videos on data science! 💭Share your thoughts, experiences, or questions in the comments below. I love hearing from you! ⌚Time Stamps⌚ 00:00 - Intro 00:36 - The Problem with Convolution 05:10 - What is translation variance? 07:46 - What is Pooling? 13:05 - Pooling Demo 15:01 - Pooling on Volumes 16:37 - KERAS Demo 18:14 - Advantages of Pooling 22:47 - Types of Pooling 25:36 - Disadvantages of Pooling 27:42 - Outro