توضیحات
training, and deployment of neural networks. Topics include feedforward networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, and reinforcement learning. It also covers practical implementation using popular frameworks such as TensorFlow, Keras, and PyTorch. Case studies illustrate applications in computer vision, natural language processing, speech recognition, and predictive analytics. Designed for students, data scientists, and AI practitioners, Deep Learning equips readers with both the theoretical foundation and practical skills necessary to build and optimize modern AI systems.
نقد و بررسیها
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