CNN, ReLU, and Dropout | Solved Example | Convolution Neural Networks скачать в хорошем качестве

CNN, ReLU, and Dropout | Solved Example | Convolution Neural Networks

In this video, you will understand the various topics related to Convolution Neural Network, ReLU (Rectified Linear Unit), Stride and Dropout. These concepts are discussed in context of working of Convolution in Neural Network which comprises the underlying architecture of various Machine Learning Models. I have taken various numerical examples to explain the concepts in depth. If you are facing any issues do let me know in the comment section below, I am here to help ❤️ If you found this video useful then please consider subscribing to my channel 🙏 Chapters in the video: 0:00 Introduction 0:31 Problem Statement 01:48 Convolution with Stride 03:09 Calculation of New Matrices 03:54 Resultant Matrix 04:34 Max Pooling 05:25 ReLU 06:22 Dropout (Theory) 07:35 Calculation in Dropout 09:19 Conclusion Background Music Credits (in order of use) Outro Music Credit: Spirit by Sappheiros: "Spirit by Sappheiros" is under a Creative Commons ( cc-by ) license Music promoted by BreakingCopyright: https://bit.ly/sappheiros-spirit