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www.kdnuggets.com | ||
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www.mlpowered.com
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| | | | | Blog posts and other information | |
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www.exxactcorp.com
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| | | | | [AI summary] The text provides an in-depth overview of Deep Reinforcement Learning (DRL), focusing on its key components, challenges, and applications. It explains how DRL combines reinforcement learning (RL) with deep learning to handle complex decision-making tasks. The article discusses the limitations of traditional Q-learning, such as the need for a Q-table and the issue of unstable target values. It introduces Deep Q-Networks (DQNs) as a solution, highlighting the use of experience replay and target networks to stabilize training. Additionally, the text highlights real-world applications like AlphaGo, Atari game playing, and oil and gas industry use cases. It concludes by emphasizing DRL's potential for scalable, human-compatible AI systems and its rol... | |
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www.knime.com
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| | | | | Learn what agentic AI is beyond the hype cycle, and the opportunities and limitations for implementing it. | |
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ataspinar.com
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| | | In the previous blog posts we have seen how we can build Convolutional Neural Networks in Tensorflowand also how we can use Stochastic Signal Analysis techniques to classify signals and time-series. In this blog post, lets have a look and see how we can build Recurrent Neural Networks in Tensorflow and use them to classify Signals. | ||
