July 2018
Intermediate to advanced
474 pages
13h 37m
English
The following section walks through the following steps for creating a pipeline for image classification:
from pyspark.ml.classification import LogisticRegressionfrom pyspark.ml import Pipelinevectorizer = dl.DeepImageFeaturizer(inputCol="image", outputCol="features", modelName="InceptionV3")logreg = LogisticRegression(maxIter=30, labelCol="label")pipeline = Pipeline(stages=[vectorizer, logreg])pipeline_model = pipeline.fit(trainDF)
predictDF = pipeline_model.transform(testDF) ...
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