You can convert a scikit-learn pipeline, classifier, or regressor to the Core ML format using sklearn.convert():

from sklearn.linear_model import LinearRegression
import pandas as pd

# Load data
data = pd.read_csv('houses.csv')

# Train a model
model = LinearRegression()[["bedroom", "bath", "size"]], data["price"])

# Convert and save the scikit-learn model
import coremltools as ct
coreml_model = ct.converters.sklearn.convert(
  model, ["bedroom", "bath", "size"], "price")'HousePricer.mlmodel')

For more information, see the API Reference.