This release is a pre-release and may not be stable for production use.
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
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file analytics_zoo_serving-0.12.0b2022080301-py2.py3-none-any.whl.
File metadata
- Download URL: analytics_zoo_serving-0.12.0b2022080301-py2.py3-none-any.whl
- Upload date:
- Size: 20.6 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/1.15.0 pkginfo/1.5.0.1 requests/2.23.0 setuptools/44.0.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/2.7.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fb1eaa48fe070a2384c33e32c6ade3097d6058730d3f8ed3cf801b41eae88813
|
|
| MD5 |
e2efcd5efaf4dbea8addded2c89fcabd
|
|
| BLAKE2b-256 |
e981b4d3c08004fc537699b7b1869755376fd00aeebcfc158cb9d5b85812cf70
|
