Tag: #ArtificialIntelligence
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Optimizing Deep Learning: A Comprehensive Guide to Batch Normalization
Batch Normalization (BN) is a technique used in deep learning to improve the training of deep neural networks by reducing the internal covariate shift problem. This problem occurs when the distribution of the inputs to each layer of the network changes during training, making it difficult to train the network effectively. BN addresses this issue…
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Mastering Transfer Learning: Enhancing Computer Vision with Pre-Trained Models
Transfer learning is a powerful technique in the field of deep learning, especially in computer vision, where it allows us to leverage pre-trained models to solve new tasks with limited data. In this blog post, we’ll explore transfer learning in the context of computer vision and demonstrate how it can be implemented using Python and…