H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
I tried to run it locally and run into error here:
I have uploaded the data to h2o-public-test-data/bigdata/server on S3.
The path to the dataset is now:
"https://s3.amazonaws.com/h2o-public-test-data/bigdata/server/criteo-uplift-v2.1.csv"
This dataset is from Kaggle and it can time out when trying to load the file and as a result the test will fail.
I tried to change the path to pd.read_csv and it does not work. Probably set something wrong somewhere.