Strengths
- Supports multiple data modalities including tabular, text, and images
- Easy-to-use APIs requiring minimal coding
- Strong model ensembling and stacking for improved accuracy
- Open source with active community and continuous updates
- Robust hyperparameter tuning and model selection automation
Limitations
- Can require significant computational resources for large datasets or complex models
- Less suitable for highly customized deep learning architectures
- Documentation can be technical for absolute beginners