Random Posts - ML Learning

 More random posts on ML:

https://github.com/chetan51/linguist?tab=readme-ov-file


https://github.com/chetan51/linguist

https://github.com/as3445/NuPIC-Stock-Prediction


https://github.com/ywcui1990/TrafficPrediction


https://github.com/youngminpark2559/connections_between_HTM_video_and_NuPIC_code


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https://www.cell.com/neuron/pdf/S0896-6273(17)30509-3.pdf


Reinforcement Learning

Alongside its important role in the development of deep learning,

neuroscience was also instrumental in erecting a second pillar of

contemporary AI, stimulating the emergence of the field of reinforcement learning (RL). RL methods address the problem of

how to maximize future reward by mapping states in the environment to actions and are among the most widely used tools in AI

research (Sutton and Barto, 1998). Although it is not widely

appreciated among AI researchers, RL methods were

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