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RNN, LSTM, GRU and Attention

Dive into the transformative world of neural networks with this comprehensive guide on RNN, LSTM, GRU, and Attention mechanisms. Explore how these models tackle the challenges of sequence prediction, manage long-term dependencies, and revolutionize language processing tasks. This article provides intuitive explanations, detailed visualizations, and contrasts between the architectures to enhance your understanding of their practical applications.

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Policy Gradient Methods

Understand the mathematical foundations and practical applications of optimizing policies directly through gradients, exploring episodic and continuous environments. The piece offers theoretical insights and proofs, illuminating complex concepts like the policy gradient theorem and function approximation.

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