Xcessiv vs Caffe: What are the differences?
Developers describe Xcessiv as "Fully managed web application for automated machine learning". A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python. On the other hand, Caffe is detailed as "A deep learning framework". It is a deep learning framework made with expression, speed, and modularity in mind.
Xcessiv and Caffe can be primarily classified as "Machine Learning" tools.
Some of the features offered by Xcessiv are:
- Fully define your data source, cross-validation process, relevant metrics, and base learners with Python code
- Any model following the Scikit-learn API can be used as a base learner
- Task queue based architecture lets you take full advantage of multiple cores and embarrassingly parallel hyperparameter searches
On the other hand, Caffe provides the following key features:
- Extensible code
Xcessiv and Caffe are both open source tools. Caffe with 29.2K GitHub stars and 17.6K forks on GitHub appears to be more popular than Xcessiv with 1.2K GitHub stars and 101 GitHub forks.