1. STT592-002: Intro. to Statistical Learning
Introduction
Chapter 01
Disclaimer:
"Some of the figures in this presentation are taken from "An Introduction to Statistical Learning, with applications in R"  (Springer, 2013) with permission from the authors: G. James, D. Witten,  T. Hastie and R. Tibshirani " 

2. STT592-002: Intro. to Statistical Learning
Below
Average
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(Top 50%)
Good
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Outstanding
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Exceptional *
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Unable to
Judge
Ability to master academic work
Ability in oral expression
Writing ability
Motivation and drive
Emotional stability and maturity
Self-confidence
Ability to work with others
Creativity or innovative talent
Leadership *
Problem-solving ability *
Planning Skills/Time Management *
Personal integrity *
Teaching potential

3. STT592-002: Intro. to Statistical Learning
Introduction to SLDM
Supervised or unsupervised statistical learning:
Supervised statistical learning involves building a statistical model for predicting, or estimating, an output based on one or more inputs.
With unsupervised statistical learning, there are inputs but no supervising output; nevertheless we can learn relationships and structure from such data.
Classification or clustering

4. Dataset used in the book
STT : Intro. to Statistical Learning
Dataset used in the book
Wage Data
Stock Mark Data
Gene Express Data…

5. Dataset used in the book
STT : Intro. to Statistical Learning
Dataset used in the book

6. STT592-002: Intro. to Statistical Learning
Chapter 02

7. STT592-002: Intro. to Statistical Learning
Introduction to R
Datacamp: Introduction to R
Chapter 2.3: R lab
Quiz1 on R: next Monday.