Widely used deep learning algorithms include models like Convolutional Neural Networks (CNNs) for image processing, Recurrent Neural Networks (RNNs) for sequential data like text and time series, and Transformers, which power modern NLP tools like ChatGPT. Generative Adversarial Networks (GANs) are also popular for creating realistic synthetic data. These algorithms enable advanced applications in computer vision, speech recognition, natural language processing, and more, making them foundational to the rapid progress in artificial intelligence today.
Widely used deep learning algorithms include models like Convolutional Neural Networks (CNNs) for image processing, Recurrent Neural Networks (RNNs) for sequential data like text and time series, and Transformers, which power modern NLP tools like ChatGPT. Generative Adversarial Networks (GANs) are also popular for creating realistic synthetic data. These algorithms enable advanced applications in computer vision, speech recognition, natural language processing, and more, making them foundational to the rapid progress in artificial intelligence today.
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