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Task 1: Import dataset

In this tutorial, we'll be working with the Consumer Complaint Resolution dataset from Kaggle. This dataset contains information about customer complaints in the banking sector, including complaint narratives, product types, issues reported, and resolution outcomes.

Our objective is to analyze complaint data and build a machine learning model using H2O Driverless AI to predict whether a customer will dispute the resolution of their complaint.

Let's import the dataset.

  1. Click + ADD DATASET (OR DRAG & DROP).
  2. Select AMAZON S3.
  3. In the Explore Amazon S3 box, enter the following S3 URI:
    s3://data.h2o.ai/DAI-Tutorials/
  4. Select the following two datasets: consumer_complaint_resolution_train.csv and consumer_complaint_resolution_test.csv.
  5. Click CLICK TO IMPORT SELECTION.

Congratulations, you have successfully imported the dataset into H2O Driverless AI. In Task 2, we will explore the dataset to understand each column.

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