H2O AutoML Is All You Need

Explore how to use H2O AutoML to automate building, tuning, and selecting machine learning models for classification tasks. Understand key parameters, model evaluation, and best practices to efficiently train diverse models and interpret leaderboard results.

We'll cover the following...

What is H2O AutoML?
H2O AutoML parameters
Train H2O AutoML
- H2O AutoML best practices

What is H2O AutoML?

There is no one-size-fits-all algorithm that can be applied to every machine learning problem. The performance of a model is highly dependent on the specific characteristics of the dataset and the problem to be solved. This is why H2O AutoML was created.

H2O AutoML is an automated machine learning tool that can build and tune many models in parallel to achieve the best performance for a given predictive modeling problem. It can handle various machine learning tasks such as classification, regression, and time series ...

1.Introduction to Machine Learning

2.Supervised Learning: Regression Models with H2O

3.Supervised Learning: Classification Models with H2O

4.Unsupervised Learning: Clustering with H2O

5.Unsupervised Learning: Anomaly Detection with H2O

6.Closing Notes

7.Appendix

H2O AutoML Is All You Need

What is H2O AutoML?