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OpenVINO vs Neptune: What are the differences?
OpenVINO: A free toolkit facilitating the optimization of a Deep Learning model. It is a comprehensive toolkit for quickly developing applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends CV workloads across Intel® hardware, maximizing performance; 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.
OpenVINO and Neptune belong to "Machine Learning Tools" category of the tech stack.
Some of the features offered by OpenVINO are:
- Optimize and deploy deep learning solutions across multiple Intel® platforms
- Accelerate and optimize low-level, image-processing capabilities using the OpenCV library
- Maximize the performance of your application for any type of processor
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 OpenVINO
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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
