from autogluon.tabular import TabularPredictor, TabularDataset

# Load the dataset
train_df = TabularDataset('train.csv')

# Define custom hyperparameters
hyperparameters = {
    'GBM': {'num_boost_round': 200},
    'NN': {'epochs': 10},
    'RF': {'n_estimators': 100},
}

# Train the model with custom settings
predictor = TabularPredictor(
    label='Target',
    eval_metric='accuracy',
    verbosity=2
).fit(
    train_data=train_df,
    hyperparameters=hyperparameters
)