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What is Reinforcement Learning?

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Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By employing positive reinforcement and punishments, businesses can teach machines to optimise actions and learn from rewards, enabling autonomous decision-making in dynamic situations.

Other Definitions

Generative Adversarial Networks (GANs)

Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used…

Decision Trees

Decision Trees are Machine Learning models that use a branching structure to make decisions or predictions. By determining the most important features and creating…

Synthetic Data

Synthetic Data is artificially generated data that mimics real-world data. Synthetic data can be used to train Machine Learning models when real data is…

Deep Learning

Deep Learning, a subfield of AI, leverages neural networks with numerous interconnected layers to process vast amounts of data, enabling machines to learn and…
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