Open-source AutoML that trains and ranks models for you.
2 months ago
AutoML is great for getting a quick result, but I find it crucial to use H2O's explainability tools to understand *why* the model is making its predictions. Without that, it's just a black box that's hard to trust for business-critical applications. The tool provides the explainability, but it's on you to use it.
8 months ago
For any kind of CSV or database table, H2O is a beast. It handles classification and regression tasks beautifully. However, for NLP or computer vision tasks, it's not the right tool. You'd be better off with a dedicated library like Hugging Face or PyTorch. But for 90% of business problems (churn, fraud, forecasting), it's perfect.
10 months ago
As a data scientist, H2O AutoML is my first step on any new tabular data project. In under an hour, it runs dozens of models and gives me a leaderboard of what works best. The stacked ensembles it creates almost always outperform a single tuned model. It saves me weeks of manual grid searching. Being open-source is a huge plus.
