Analytics Zoo: A unified Data Analytics and AI platform for distributed TensorFlow, Keras, PyTorch, Apache Spark/Flink and Ray.
You may want to develop your AI solutions using Analytics Zoo if:
- You want to easily prototype the entire end-to-end pipeline that applies AI models (e.g., TensorFlow, Keras, PyTorch, BigDL, OpenVINO, etc.) to production big data.
- You want to transparently scale your AI applications from a laptop to large clusters with "zero" code changes.
- You want to deploy your AI pipelines to existing YARN or K8S clusters WITHOUT any modifications to the clusters.
- You want to automate the process of applying machine learning (such as feature engineering, hyperparameter tuning, model selection and distributed inference).
Find instructions to install analytics-zoo via pip, please visit our documentation page: https://analytics-zoo.github.io/master/#PythonUserGuide/install/
For source code and more information, please visit our GitHub page: https://github.com/intel-analytics/analytics-zoo
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Release files for analytics-zoo-serving 0.11.2
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| File | Interpreter | ABI | Platform | Reset |
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| analytics_zoo_serving-0.11.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Release files / analytics_zoo_serving-0.11.2-py2.py3-none-any.whl
| Download URL | analytics_zoo_serving-0.11.2-py2.py3-none-any.whl |
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| Size | 18.2 kB |
| Tags | Python 2 Python 3 |
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