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Slalom_Tobias
by • New Contributor III
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Resolved! ML Practioner | ML 11 - XGBoost notebook | cannot import keras.applications.resnet50

the following code...from sparkdl.xgboost import XgboostRegressorfrom pyspark.ml import Pipelineparams = {"n_estimators": 100, "learning_rate": 0.1, "max_depth": 4, "random_state": 42, "missing": 0}xgboost = XgboostRegressor(**params)pipeline = Pipel...

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Prabakar
Esteemed Contributor III
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You need to choose the runtime for ML instead of the standard.

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Slalom_Tobias
by • New Contributor III
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Resolved! ML Practioner | ml 09 - automl notebook | error on importing databricks.automl

executing the following code...from databricks import automlsummary = automl.regress(train_df, target_col="price", primary_metric="rmse", timeout_minutes=5, max_trials=10)generates the error...ImportError: cannot import name 'automl' from 'databricks...

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Krueger156
New Contributor II
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I'm happy to see a particularly subject.

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Slalom_Tobias
by • New Contributor III
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Resolved! ML Practioner | ML 10 - Feature Store notebook | feature_store import error

the following code...from pyspark.sql.functions import monotonically_increasing_id, lit, expr, randimport uuidfrom databricks import feature_storefrom pyspark.sql.types import StringType, DoubleTypefrom databricks.feature_store import feature_table, ...

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Anonymous
Not applicable
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Hope that was an easy fix - @Tobias Cortese​ ! Thanks for marking the "best answer"!

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