# Obviously Awesome

# Data Mining with Excel ## Intro - Some Skills - example 1a
- example 1b
- Formulas, Autofill vs copy, Absolute references, Paste, IF functions ## Linear Regression (LR) - Intro - Example - example 1a
- example 1b
- example 2a
- example 2b
- Multiple LR ## K-Means Clustering - Intro - Example - example 1a
- example 1b
- Assignment
## Linear Discriminant Analysis (LDA) - Intro - Solver - Example - example 1a
- example 1a
## Cross Validation & ROC Analysis - Intro - Cross Validation - ROC Analysis - Example - CV: example 1a
- CV: example 1b
- CV: example 1c
- ROC: example 1a
- ROC: example 1a
## Logistic Regression - Intro - Example - example 1a
- example 1b
## K-Nearest Neighbors - Intro - Example - Exercise 1 - example 1a
- example 1b
- Exercise 2 - example 2a
- example 2b
- Exercise 3 - example 3a
- example 3b
- Exercise 4 - example 4a
- example 4b
## Naive Bayes Classification - Intro - Example - Exercise 1 - example 1a
- example 1b
- Exercise 2 - example 2a
- example 2b
## Decision Trees - Intro - Example - example 1a
- example 1b
- example 1b IFERROR
- A better approach - example 2a
- example 2b
- example 2b IFERROR
- Applying the model - example 3a
- example 3b
## Association Analysis - Intro - Example - example 1a
- example 1b
- example 2b
## Neural Nets - Intro - Example - Experiment 1 - example 1a
- example 1b
- example 2a
- example 2b
- example 2b w/o Opt.
- Experiment 2 ## Text Mining - Intro / General Understanding - file 1a contains a dictionary with stop words, some positive & negative keywords (along with some negated 2-gram phrases), and a polarity score for each. - example 1a
- example 1b
- example 1c
## After Excel