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Neural networks and deep learning

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Deep Learning

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🧠Deep Learning

Neural Networks Explained: Building Blocks of Deep Learning

Neural Networks are the foundation of modern deep learning and AI. This detailed guide explains how neural networks work, from basic neurons and activation functions to advanced architectures like CNNs, RNNs, Transformers, and GANs. Learn about forward propagation, backpropagation, optimization algorithms like Adam, and essential training techniques including regularization, batch normalization, and transfer learning. Master the fundamentals needed to build and train effective deep learning models.

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Understanding Transformer Architecture: The Foundation of Modern AI
🧠Deep Learning

Understanding Transformer Architecture: The Foundation of Modern AI

The Transformer architecture has revolutionized deep learning since 2017. This comprehensive guide explores self-attention mechanisms, multi-head attention, and how Transformers power modern AI models like GPT-4, BERT, and Vision Transformers. Learn about the key components, real-world applications, and why Transformers have become the backbone of breakthrough AI systems in NLP, computer vision, and multimodal understanding

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