Python Scikit-Learn Library

Meet sklearn

scikit-learn.org

scikit-learn tutorial

Scikit-learn user guide

import sklearn as sk
sklearn.__version__
import nose
nosetest sklearn -exe

SkLearn Basics

Compliments and extend scipy

Classification

Regression

clustering

Dimensionality reduction

Example

from sklearn import datasets
iris = datasets.load_iris()
digits = datasets.load_digits()
print(digits.data)
from sklearn import svm
clf = svm.SVC(gamma=0.001, C=100)
clf.fit(digits.data[:-1], digits.target[:-1])
clf.predict(digits.data[-1:])

Example

# Install a pip package in the current Jupyter kernel
import sys
!{sys.executable} -m pip install mglearn

Example

from sklearn.linear_model import LinearRegression
# Training data
X = [[7], [8], [10], [14], [18]]
y = [[8], [9], [13], [17.5], [20]]
# Create and fit the model
model = LinearRegression()
model.fit(X, y)
print 'Predict value: $%.2f' % model.predict([12])[0]