Gluon vs Skyl.ai
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Detailed Comparison
A new open source deep learning interface which allows developers to more easily and quickly build machine learning models, without compromising performance. Gluon provides a clear, concise API for defining machine learning models using a collection of pre-built, optimized neural network components. | Build & deploy ML models faster on unstructured data. No specialized skills required. Easy-to-use & scalable SaaS platform. |
Simple, Easy-to-Understand Code: Gluon offers a full set of plug-and-play neural network building blocks, including predefined layers, optimizers, and initializers.;Flexible, Imperative Structure: Gluon does not require the neural network model to be rigidly defined, but rather brings the training algorithm and model closer together to provide flexibility in the development process.;Dynamic Graphs: Gluon enables developers to define neural network models that are dynamic, meaning they can be built on the fly, with any structure, and using any of Python’s native control flow.;High Performance: Gluon provides all of the above benefits without impacting the training speed that the underlying engine provides. |
Collect, label, and visualize unstructured data;
Guided modules to upload, clean, label, and visualize unstructured data;
Create & train models automatically;
Train models without coding using our ready-made, fine tuned, state-of-the-art neural network architecture;
Monitor model performance and iterate in minutes;
Monitor data collection, labeling, training, and performance of deployed models in real-time |
Statistics | |
GitHub Stars 2.3K | GitHub Stars - |
GitHub Forks 219 | GitHub Forks - |
Stacks 29 | Stacks 0 |
Followers 80 | Followers 7 |
Votes 3 | Votes 0 |
Pros & Cons | |
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What are some alternatives to Gluon, Skyl.ai?
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scikit-learn
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MLflow
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