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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 on August 30th, 2017 0 likes 86 plays 0  

DSPA Chapter 20 Prediction and Internal Statistical Cross-validation

Chapter 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 on August 30th, 2017 0 likes 35 plays 0  

DSPA Chapter 19 Text Mining (TM) and Natural Language Processing (NLP)

DSPA Chapter 19 Text Mining (TM) and Natural Language Processing (NLP)Natural Language Processing (NLP) and Text Mining (TM) refer to automated machine-driven algorithms for semantically mapping,…

From  Tina Chang on July 17th, 2017 0 likes 58 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 on July 17th, 2017 0 likes 23 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 of…

From  Tina Chang on July 17th, 2017 0 likes 27 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 on July 17th, 2017 0 likes 57 plays 0  

DSPA Chapter 6: k-Nearest Neighbors Classification

DSPA Chapter 6: k-Nearest Neighbors Classification In the next several chapters we will concentrate of various progressively advanced machine learning, classificaiton and clustering techniques.…

From  Tina Chang on July 17th, 2017 0 likes 83 plays 0  

DSPA Chapter 9: Regression Classification

DSPA Chapter 9: Regression Classification In previous chapters (6, 7, and 8), we covered some classification methods that use mathematical formalism to address everyday life prediction problems.…

From  Tina Chang on July 17th, 2017 0 likes 65 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 on July 17th, 2017 0 likes 66 plays 0