JakubWhat is Neptune?
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.
Neptune is a tool in the AI Infrastructure category of a tech stack.
Key Features
Experiment trackingExperiment versioningExperiment comparisonExperiment monitoringExperiment sharingNotebook versioning
Neptune Pros & Cons
Pros of Neptune
- ✓Aws managed services
- ✓Supports both gremlin and openCypher query languages
Cons of Neptune
- ✗Doesn't have much community support
- ✗Doesn't have much support for openCypher clients
- ✗Doesn't have proper clients for different lanuages
Neptune Alternatives & Comparisons
What are some alternatives to Neptune?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
