Lobe vs PredictionIO: What are the differences?
Developers describe Lobe as "Deep learning made simple". An easy-to-use visual tool that lets you build custom deep learning models, quickly train them, and ship them directly in your app without writing any code. On the other hand, PredictionIO is detailed as "Open Source Machine Learning Server". PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
Lobe and PredictionIO can be categorized as "Machine Learning" tools.
Some of the features offered by Lobe are:
- Build - Drag in your training data and Lobe automatically builds you a custom deep learning model. Then refine your model by adjusting settings and connecting pre-trained building blocks.
- Train - Monitor training progress in real-time with interactive charts and test results that update live as your model improves. Cloud training lets you get results quickly, without slowing down your computer.
- Ship - Export your trained model to TensorFlow or CoreML and run it directly in your app on iOS and Android. Or use the easy-to-use Lobe Developer API and run your model remotely over the air.
On the other hand, PredictionIO provides the following key features:
- Integrated with state-of-the-art machine learning algorithms. Fine-tune, evaluate and implement them scientifically.
- Customize the modularized open codebase to fulfill any unique prediction requirement.
- Built on top of scalable frameworks such as Hadoop and Cascading. Ready to handle data of any scale.
PredictionIO is an open source tool with 11.8K GitHub stars and 1.92K GitHub forks. Here's a link to PredictionIO's open source repository on GitHub.