Understanding Convolutional Neural Networks: Mechanisms and Kernel Operations
This video explains how Convolutional Neural Networks (CNNs) process data and generate feature maps, with a focus on the role of kernels in feature extraction.
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About this video
Ever wondered how Convolutional Neural Networks (CNNs) process data and generate feature maps? In this video, we dive into the workings of CNNs, focusing on how kernels (or filters) slide across the input layer, perform element-wise multiplications, and create feature maps. Discover how strides influence the size of these maps and follow the steps from generating outputs like Z1 and Z2 to flattening feature maps into predictions. Perfect for anyone looking to understand the core mechanics of CNNs and their role in deep learning!
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Hash Tags: #CNN #NeuralNetworks #DeepLearning #MachineLearning #AI #ComputerVision #TensorFlow #PyTorch #DataScience #MLAlgorithms #ArtificialIntelligence #TechEducation #LearnToCode #CodingTutorials
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28.6K
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497
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Duration
1:00
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Published
Sep 17, 2024
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hd
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#code monarch #coding #coding monarch #youtube #monarch code #Convolutional Neural Networks #CNN #how CNNs work #feature maps #kernels #filters #stride in CNN #CNN forward pass #deep learning #machine learning #AI #artificial intelligence #neural networks #image processing #element-wise multiplication #prediction in CNN #flattening feature maps #Code Monarch #neural #networks #convolutional #forward #propagation #feature #maps #backpropagation #gradient #descent #deep #learning
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