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XGBoost vs Neptune: What are the differences?
What is XGBoost? Scalable and Flexible Gradient Boosting. Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow.
What is Neptune? The most lightweight experiment tracking tool for machine learning. It brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed, reproduced and shared with others. Works with all common technologies and integrates with other tools.
XGBoost belongs to "Python Build Tools" category of the tech stack, while Neptune can be primarily classified under "Machine Learning Tools".
Some of the features offered by XGBoost are:
- Flexible
- Portable
- Multiple Languages
On the other hand, Neptune provides the following key features:
- Experiment tracking
- Experiment versioning
- Experiment comparison
Pros of Neptune
- Aws managed services1
- Supports both gremlin and openCypher query languages1
Pros of XGBoost
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Cons of Neptune
- Doesn't have much support for openCypher clients1
- Doesn't have proper clients for different lanuages1
- Doesn't have much community support1