Search for tag: "probability calculus"

DSPA Chapter 22 Deep Learning

Chapter 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 0 likes 109 plays 0  

DSPA Chapter 21 Function Optimization

Chapter 21 covers (1) constrained and unconstrained optimization, (2) Lagrange multipliers, (3) linear, quadratic and (general) non-linear programming, and (4) data denoising.

From  Tina Chang 0 likes 29 plays 0  

DSPA Chapter 17 (Regularized Linear Modeling and Controlled Variable Selection)

DSPA Chapter 17 (Regularized Linear Modeling and Controlled Variable Selection) Classical techniques for choosing important covariates to include in a model of complex multivariate data relied on…

From  Tina Chang 0 likes 33 plays 0  

DSPA Chapter 13 Model Evaluation

DSPA 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 0 likes 44 plays 0  

DSPA Chapter 14 Improvement of Model Performance

DSPA 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 0 likes 24 plays 0  

DSPA Chapter 8 Decision Tree Classification

DSPA Chapter 8 Decision Tree Classification In this chapter, we will (1) see a simple motivational example of decision trees based on the Iris data, (2) describe decision-tree divide and conquer…

From  Tina Chang 0 likes 94 plays 0  

DSPA Chapter 7 Naive Bayes Classification

DSPA Chapter 7 Naive Bayes Classification Please review the introduction to Chapter 6, where we described the types of machine learning methods and presented lazy classification for numerical…

From  Tina Chang 0 likes 93 plays 0