So what’s getting unbiquitous and cheap?
Data.
And what is complementary to data?
Analysis.
-Hal Varian
Netflix Prize Competition
EDA:electronic design automation
Television Size Over the Years
from sklearn.datasets import make_classification from sklearn.linear_model import LogisticRegression X, y = make_classification(n_samples=10000, n_features=10, n_classes=2, n_informative=5) Xtrain = X[:9000] Xtest = X[9000:] ytrain = y[:9000] ytest = y[9000:] clf = LogisticRegression() clf.fit(Xtrain, ytrain)