Search for tag: "artificial intelligence"
DSPA Chapter 22 Deep LearningChapter 22 demonstrates the R deep learning package MXNetR and demonstrate state-of-the-art deep learning models utilizing CPU and GPU for fast training (learning) and testing (validation).
From Tina Chang
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DSPA Chapter 20 Prediction and Internal Statistical Cross-validationChapter 20 uses Google Flu Trends, Autism, and Parkinson’s disease case-studies to illustrate (1) alternative forecasting types using linear and non-linear predictions, (2) exhaustive and…
From Tina Chang
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DSPA Chapter 13 Model EvaluationDSPA Chapter 13 Model Evaluation In this chapter, we will discuss (1) various evaluation strategies for prediction, clustering, classification, regression, and decision trees, (2) visualization…
From Tina Chang
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DSPA Chapter 14 Improvement of Model PerformanceDSPA Chapter 14 Improvement of Model Performance We already explored several alternative machine learning (ML) methods for prediction, classification, clustering and outcome forecasting. In many…
From Tina Chang
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