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Application of Reinforcement Learning in 5G MillimetreWave NetworksArtmiz GolkaramnayA Thesis in The Department of Electrical and Computer EngineeringPresented in Partial Fulfillment of the Requirements

How to fill out application of reinforcement learning

How to fill out application of reinforcement learning

1. Understand the problem and define the goals of the reinforcement learning application.
2. Select the appropriate reinforcement learning algorithm based on the problem at hand.
3. Collect and preprocess the data needed for training the reinforcement learning model.
4. Train the model using an iterative process of taking actions, observing rewards, and updating the model.
5. Evaluate the performance of the trained model and fine-tune it if necessary.
6. Deploy the trained reinforcement learning model in the target environment and monitor its performance.

Who needs application of reinforcement learning?

1. Researchers in artificial intelligence and machine learning looking to develop advanced algorithms.
2. Companies in industries such as robotics, gaming, finance, healthcare, and marketing seeking to implement personalized decision-making systems.
3. Academics and students studying reinforcement learning for research or educational purposes.

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