Data Science

Credit to Adam Green - adgefficiency.com

• research = worry about models
• actual applications = worry about data
• this course is about the data

Course notes

visualization.ipynb

• matplotlib APIs
• t-SNE & PCA

data-cleaning.ipynb

• cleaning columns in place
• work that has to be done

feature-engineering.ipynb

• adding new columns
• optional work that improves performance

linear-models.ipynb

[imbalanced-classes.ipynb]

model-selection.ipynb

• what models to try

model-evaluation.ipynb

• how to select a model
• hyperparameter tuning

interpretation.ipynb

• linear model coefficients
• LIME

feature-selection.ipynb

• univariate
• stability selection

Where to find data

NIMH Data Archive - National Institute of Mental Health Data Archive (NDA) makes available human subjects data collected from hundreds of research projects across many scientific domains

StatLib Datasets Archive

Kaggle Datasets

Internet archive - non-profit library of millions of free books, movies, software, music, websites, and more

r/datasets

Programmable Web - API's

UCI Machine Learning Repository

Common crawl - an open repository of web crawl data that can be accessed and analyzed by anyone

List of datasets for machine-learning research - Wikipedia