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DSPA Chapter 22 Deep Learning duration 39 minutes 38 seconds DSPA Chapter 22 Deep Learning DSPA Chapter 22 Deep Learning	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). examinations +18 More From Tina Chang 0 likes 111 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date August 29th, 2017
DSPA Chapter 20 Prediction and Internal… duration 31 minutes 4 seconds DSPA Chapter 20 Prediction and Internal… DSPA Chapter 20 Prediction and Internal Statistical Cross-validation	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… examinations +18 More From Tina Chang 0 likes 41 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date August 29th, 2017
DSPA Chapter 19 Text Mining (TM) and Natural… duration 54 minutes 28 seconds DSPA Chapter 19 Text Mining (TM) and Natural… DSPA Chapter 19 Text Mining (TM) and Natural Language Processing (NLP)	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,… text mining +16 More From Tina Chang 0 likes 69 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date July 1st, 2017
DSPA Chapter 17 (Regularized Linear Modeling and… duration 48 minutes 40 seconds DSPA Chapter 17 (Regularized Linear Modeling and… DSPA Chapter 17 (Regularized Linear Modeling and Controlled Variable Selection)	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… examinations +16 More From Tina Chang 0 likes 36 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date July 1st, 2017
DSPA Chapter 13 Model Evaluation duration 33 minutes 31 seconds DSPA Chapter 13 Model Evaluation DSPA Chapter 13 Model Evaluation	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… examinations +14 More From Tina Chang 0 likes 46 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date August 1st, 2017
DSPA Chapter 8 Decision Tree Classification duration 49 minutes 2 seconds DSPA Chapter 8 Decision Tree Classification DSPA Chapter 8 Decision Tree Classification	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… and disorders +18 More From Tina Chang 0 likes 98 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date August 1st, 2017
DSPA Chapter 6: k-Nearest Neighbors Classification duration 30 minutes 36 seconds DSPA Chapter 6: k-Nearest Neighbors Classification DSPA Chapter 6: k-Nearest Neighbors Classification	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.… examinations +16 More From Tina Chang 0 likes 157 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits S Creation Date August 1st, 2017
DSPA Chapter 9: Regression Classification duration 28 minutes 47 seconds DSPA Chapter 9: Regression Classification DSPA Chapter 9: Regression Classification	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.… mathematical sciences +16 More From Tina Chang 0 likes 91 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date August 1st, 2017
DSPA Chapter 7 Naive Bayes Classification duration 18 minutes 23 seconds DSPA Chapter 7 Naive Bayes Classification DSPA Chapter 7 Naive Bayes Classification	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… mathematical sciences +16 More From Tina Chang 0 likes 97 plays 0 Stewardship SOCR Resource, University of Michigan Rights CC-BY Credits SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date August 1st, 2017