GitHub / mrodriguezsanz / DeepLearningAI-DeepLearningSpecialization

Participants in this Specialization have the opportunity to construct and train various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Transformers. They learn to enhance these networks with techniques such as Dropout, BatchNorm, Xavier/He initialization, among others.

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Topics: artificial-neural-networks, attention-models, backpropagation, convolutional-neural-networks, decision-making, deeplearning, facial-recognition, gated-recurrent-unit, hyperparameter-tuning, inductive-transfer, long-short-term-memory, multi-task-learning, natural-language-processing, neural, neural-network-architectures, object-detection, python, python-programming, recurrent-neural-network, tensorflow

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