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Using Machine Learning to analyze and predict the effect of different CPU features on CPU benchmarks for edge computing Ling Y1, Media S2 Submitted: December 29, 2022, Revised: version 1, February

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How to fill out using machine learning to

1. Gather and preprocess data for training
2. Select a machine learning algorithm appropriate for the task
3. Split the data into training and testing sets
4. Train the model on the training set
5. Evaluate the model on the testing set
6. Tune hyperparameters to improve performance
7. Deploy the trained model for making predictions

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2. Businesses seeking to optimize processes and make data-driven decisions
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4. Government agencies interested in predicting trends and patterns

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Using machine learning refers to the application of algorithms and statistical models to enable computers to perform specific tasks without explicit instructions, improving predictive accuracy and automating processes.

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Individuals and organizations that engage in data-driven decision-making, predictive analysis, or any applications that involve machine learning techniques may be required to file reports detailing their use of these technologies, depending on regulatory requirements.

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Reports on using machine learning typically must include methodologies employed, data sources utilized, results obtained, any biases detected, and potential implications of the findings.