See also: the course schedule on Learning Suite.

Note: the PowerPoint slides also contain hidden slides that were not used in class.

! Date	PDF	PowerPoint	Screencast	Supplement	Title
1	9/3/2014	PDF	PPTX	—	—	Course Introduction; Review of Prob. Theory
2	9/5/2014	PDF	PPTX	—	—	Independence, Conditional Independence
3	9/8/2014	PDF	PPTX	—	—	Bayes Law, Rule of Total Probability
4	9/10/2014	PDF	PPTX	—	—	Random Variables, Expected Values
-	9/10/2014	PDF	PPTX	All	—	Bonus lecture on iteration in mathematical expressions
5	9/12/2014	PDF	PPTX	—	—	Properties of Random Variables; Marginalization Revisted
6	9/15/2014	PDF	PPTX	—	—	Useful Distributions; Reasoning with Joint Distributions
7	9/17/2014	PDF	PPTX	—	—	Reasoning with Joint Distributions; Bayes Nets
8	9/19/2014	PDF	PPTX	All	—	Conditional Independence in Bayes Nets; Joint Queries of Bayes Nets
9	9/22/2014	PDF	PPTX	—	—	Answering Queries on Bayes Nets
10	9/24/2014	PDF	PPTX	All	Example 1 Example 2	Bayes Nets (cont.); Reading influence in Bayes Nets
11	9/26/2014	PDF	PPTX	All	—	Intro. to Naive Bayes
12	9/29/2014	PDF	PPTX	—	—	Alternative Event Models for Naive Bayes; Class-Conditional Language Models
13	10/1/2014	PDF	PPTX	—	PDF, PPTX	Maximum Likelihood Estimation for the Categorical Distribution (and Naive Bayes) using Lagrange Multipliers
14	10/3/2014	PDF	PPTX	All	—	Expressing Uncertainty about Parameters; Beta and Dirichlet Distributions
15	10/6/2014	PDF	PPTX	—	—	Conjugate Priors: Beta-Binomial Conjugacy, Dirichlet-Multinomial Conjugacy; Bayesian Learning
16	10/8/2014	PDF	PPTX	—	—	Maximum a Posteriori Estimation for the Categorical Distribution (and for Naive Bayes)
17	10/10/2014	PDF	PPTX	—	—	Mixture Models; Mixture of Multinomials Model; Generative Stories
18	10/13/2014	PDF	PPTX	—	—	Text Clustering with Expectation Maximization
-	10/15/2014	—	—	—	—	Review for Mid-Term Exam
19	10/20/2014	PDF	PPTX	—	—	Initialization for Expectation Maximization; Glimpse of Hierarchical Bayesian Models
20	10/22/2014	PDF	PPTX	—	—	Gaussian Mixture Models
-	10/24/2014	—	—	—	—	Mid-Term Exam Follow-up
21	10/27/2014	PDF	PPTX	—	—	Gaussian Mixture Models (cont.)
22	10/29/2014	PDF	PPTX	—	—	Sequence Labeling; Part of Speech Tagging; Hidden Markov Models
23	10/31/2014	PDF	PPTX	—	—	Hidden Markov Models; Viterbi Algorithm
24	11/3/2014	PDF	PPTX	—	—	Overview of Speech Recognition: Noisy Channel Model, DSP, Front End / Feature Extraction
25	11/5/2014	PDF	PPTX	All	—	Overview of Speech Recognition: using Hidden Markov Models with Gaussian Mixture Models as Acoustic Models, Markov Chains as Language Models, Lexicon, Decoding
26	11/7/2014	PDF	PPTX	All	—	Monte Carlo Principle; Intro. to Gibbs Sampling
-	11/10/2014	—	—	—	—	Q&A
27	11/12/2014	PDF	PPTX	—	Video	Document Clustering with Gibbs Sampling on a Mixture of Multinomials
28	11/14/2014	PDF	PPTX	—	Video	Document Clustering with Gibbs Sampling: Metrics and Results
29	11/17/2014	PDF	PPTX	—	—	Introduction to Topic Modeling; Latent Dirichlet Allocation (LDA)
30	11/19/2014	PDF	PPTX	—	—	Latent Dirichlet Allocation: Inference with Gibbs Sampling
31	11/21/2014	PDF	PPTX	—	PDF; PPTX	Latent Dirichlet Allocation: Inference with Gibbs Sampling (cont.)
32	11/24/2014	PDF	PPTX	—	—	Limitations of Joint Models; Motivating Conditional Models; Word Sense Disambiguation
33	11/25/2014	PDF	PPTX	—	—	Features for Word Sense Disambiguation; Limitations of Joint Models; Motivating Conditional Models
34	12/1/2014	PDF	PPTX	—	—	Maximum Entropy Models
35	12/3/2014	PDF	PPTX	—	—	Maximum Entropy Models for Text Classification; Feature Engineering
36	12/5/2014	PDF	PPTX	—	Ocular Presentation	Application of Course Ideas to Historical OCR; Preview of CS 679 (NLP)

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BYU CS users also have full access to the posted lecture slides via the CS department file-system. Connect to schizo, and check the following directory:

 /users/home1/faculty/ringger/public_html/Fall2014-CS401R/lectures

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