10/15/24, 9:10 ISYE 6501 (Full Course)
AM Notes
about:blan 1/
k 85
,10/15/24, 9:10 ISYE 6501 (Full Course)
AM Notes
Week 1
Why Analytics? 6
Data Vocabulary 7
Classification 8
Support Vector Machines 11
Scaling and Standardization 13
k-Nearest Neighbor (KNN) 13
Week 2
Model Validation 16
Validation and Test Sets 17
Splitting the Data 18
Cross-Validation 20
Clustering 21
Supervised vs. Unsupervised Learning 22
Week 3
Data Preparation 25
Introduction to Outliers 25
Change Detection 27
Week 4
Time Series Data 31
AutoRegressive Integrated Moving Average (ARIMA) 34
Generalized Autoregressive Conditional Heteroskedasticity (GARCH) 34
Week 5
Regression 37
Regression Coefficients 39
Causation vs. Correlation 39
Important Indicators in the Output 40
Week 6
De-Trending 43
about:blan 2/
k 85
,10/15/24, 9:10 ISYE 6501 (Full Course)
AM Notes
about:blan 3/
k 85
, 10/15/24, 9:10 ISYE 6501 (Full Course)
AM Notes
Elements of Optimization Models 74
Modeling with Binary Variables 74
Week 11
Optimization for Statistical Models 76
Classification of Optimization Models 79
Stochastic Optimization 81
Basic Optimization Algorithms 82
Non-Parametric Models 82
Bayesian Modeling 83
Communities in Graphs 83
Neural Networks and Deep Learning 84
Competitive Models 86
about:blan 4/
k 85
AM Notes
about:blan 1/
k 85
,10/15/24, 9:10 ISYE 6501 (Full Course)
AM Notes
Week 1
Why Analytics? 6
Data Vocabulary 7
Classification 8
Support Vector Machines 11
Scaling and Standardization 13
k-Nearest Neighbor (KNN) 13
Week 2
Model Validation 16
Validation and Test Sets 17
Splitting the Data 18
Cross-Validation 20
Clustering 21
Supervised vs. Unsupervised Learning 22
Week 3
Data Preparation 25
Introduction to Outliers 25
Change Detection 27
Week 4
Time Series Data 31
AutoRegressive Integrated Moving Average (ARIMA) 34
Generalized Autoregressive Conditional Heteroskedasticity (GARCH) 34
Week 5
Regression 37
Regression Coefficients 39
Causation vs. Correlation 39
Important Indicators in the Output 40
Week 6
De-Trending 43
about:blan 2/
k 85
,10/15/24, 9:10 ISYE 6501 (Full Course)
AM Notes
about:blan 3/
k 85
, 10/15/24, 9:10 ISYE 6501 (Full Course)
AM Notes
Elements of Optimization Models 74
Modeling with Binary Variables 74
Week 11
Optimization for Statistical Models 76
Classification of Optimization Models 79
Stochastic Optimization 81
Basic Optimization Algorithms 82
Non-Parametric Models 82
Bayesian Modeling 83
Communities in Graphs 83
Neural Networks and Deep Learning 84
Competitive Models 86
about:blan 4/
k 85
