Intro to Data Science
About the Authors
Getting Started
0.1
Introduction to Data Science
0.2
A Brief History of Data Science
0.3
A Brief Introduction to Python
1
The Data Pipeline
1.1
Project Idea
1.2
Data Acquisition
1.3
Preprocessing
1.4
Analysis
1.5
Presentation
2
Data Preprocessing
2.1
Descriptive Analysis
2.1.1
Measures of central tendency
2.1.2
Measures of variability
2.1.3
Visualizations
2.1.4
Transformations
2.1.5
Correlation
2.2
Feature Scaling
2.3
Dimensionality Reduction
2.3.1
Principal component analysis (PCA)
2.3.2
t-distributed Stochastic Neighbor Embedding (tSNE)
3
Modeling and Validation
3.1
Linear models
3.2
Model Score
3.3
Model validation
An Introduction to Data Science
3.2
Model Score
mean squared error (MSE)
coefficient of determination (r-squared)