Chemistry 696D Lectures (home)
Course outline, logistics: Lecture00.pdf
"What is analytical informatics" - Between measurement and decisions Lecture01.pdf
"Statistical Decisions: Populations, Features and Classes" Lecture02.pdf
"Pattern Recognition: 'Class' Description and Distinction" Lecture03.pdf
"Using R for Data Analysis: Populations and linear regression" (In-class R demo) Lecture04.pdf
"Regression of a Response Matrix" Lecture05.pdf
"Local methods and simple comparisons" (K-nearest neighbors and comparing classifiers) Lecture06.pdf
"Mixtures and Multiple Classes" Lecture07.pdf
"Raman Classification" - by Dongmao Zhang, Lecture08 - Zhang_Raman.pdf
"Feature selection and discrimination in high dimension" (In-class Ggobi Demo) Lecture09.pdf
"Using LDA" (Also canonical variates for high dimension data display) Lecture10.pdf
"LDA, Logistic Regression and Separating Hyperplanes" (Logistic regression in R) Lecture11.pdf
"Multi-layer Neural Networks" Lecture12.pdf
"Support Vector Machines" Lecture13.pdf
"Spectroscopy-specific processing and data analysis", Lecture14.pdf
"Recursive Partitioning" - by Richard Higgs, Lecture15 - Higgs_RP.pdf
"Recursive Partitions in R" (A Lecture Supplement) Lecture15a.pdf
"Ensembles" - by Richard Higgs, Lecture16 - Higgs_Ensembles.pdf
"Unsupervised Learning: Clustering", Lecture17.pdf
"Technology of Informatics", Lecture18.pdf
"Progamming Perl" (Two part with demonstrations using ptkdb), Lecture19-20.pdf
"Chemical Structure Representation", Lecture21.pdf
"XML", Lecture22.pdf
"Relational Databases", Lecture23.pdf
"Database Programming", Lecture24.pdf
"Integrated Systems", Lecture25.pdf
"Bioinformatics Systems and High Performance Computing", Lecture26.pdf
"Case Study: High Throughput Screening by MS" - by Eric Stauffer, Lecture27_Stauffer_MS.pdf