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 www.neuralnet.ai
Asynchronous Deep Reinforcement Learning - NeuralNet.ai
| | blog.ephorie.de
Reinforcement Learning: Life is a Maze - Learning Machines
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| | [AI summary] An article explains reinforcement learning concepts using multi-armed bandit examples and a robot navigating a maze, concluding with a mention of neural networks in Google's Go-playing AI.
| | danieltakeshi.github.io
Going Deeper Into Reinforcement Learning: Understanding Deep-Q-Networks
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| | The Deep Q-Network (DQN) algorithm, as introduced by DeepMind in a NIPS 2013workshop paper, and later published in Nature 2015 can be credited withrevolution...
| | michael-lewis.com
A machine learning glossary for hackers ยท Michael I Lewis
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| | This is a short summary of some of the terminology used in machine learning, with an emphasis on neural networks. I've put it together primarily to help my own understanding, phrasing it largely in non-mathematical terms. As such it may be of use to others who come from more of a programming than a mathematical background.
| | blog.otoro.net
Neural Network Evolution Playground with Backprop NEAT |
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| [AI summary] This article describes a project that combines genetic algorithms, NEAT (NeuroEvolution of Augmenting Topologies), and backpropagation to evolve neural networks for classification tasks. The key components include: 1) Using NEAT to evolve neural networks with various activation functions, 2) Applying backpropagation to optimize the weights of these networks, and 3) Visualizing the results of the evolved networks on different datasets (e.g., XOR, two circles, spiral). The project also includes a web-based demo where users can interact with the system, adjust parameters, and observe the evolution process. The author explores how the genetic algorithm can discover useful features (like squaring inputs) without human intervention, and discusses the ...