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Deep Learning - Convolutional Neural Networks

Deep Learning - Convolutional Neural Networks

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Main Challenges in Machine Learning: 1. Insufficient or Poor-Quality Data Lack of labeled data for supervised learning. Noisy, incomplete, or biased data can lead to poor models. 2. Overfitting and Underfitting Overfitting: Model performs well on training data but poorly on new data. Underfitting: Model is too simple to capture the underlying pattern. 3. High Computational Cost Training complex models (e.g., deep learning) requires powerful hardware and GPUs. 4. Scalability Models trained on sma

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Convolution Neural Networks

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What Are Convolutional Neural Networks?

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[PDF] ImageNet classification with deep convolutional neural networks | Semantic Scholar

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