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#: ../../source/user_guide/learn/joblib.rst:5
msgid "Integrate with joblib"
msgstr "和 joblib 集成"

#: ../../source/user_guide/learn/joblib.rst:7
msgid ""
"`Joblib <https://joblib.readthedocs.io/>`_ is a library integrated with "
"`scikit-learn <https://scikit-learn.org>`_ to make machine learning jobs "
"parallel.  We create a backend for joblib with :doc:`Mars remote "
"<remote>` and users can make their scikit-learn tasks parallel with Mars."
msgstr ""
"`Joblib <https://joblib.readthedocs.io/>`_ 是一个集成在 `scikit-learn <"
"https://scikit-learn.org>`_ 中用于将机器学习任务并行化的包。在 Mars 中，"
"我们使用 :doc:`Mars remote <remote>` 为 joblib 实现了一个后端，用户可以将"
"已有的 scikit-learn 任务使用 Mars 并行化。"

#: ../../source/user_guide/learn/joblib.rst:12
msgid "To enable the backend, you need to register it with the code below."
msgstr "你可以使用下面的代码注册和使用 Mars 中的 joblib 后端。"

#: ../../source/user_guide/learn/joblib.rst:19
msgid ""
"After that, it is possible to create a Mars parallel backend with Mars "
"service endpoint or existing Mars session.  When nothing specified, "
"default or local session will be used."
msgstr ""
"完成注册后，你可以使用 Mars 服务地址或者已经创建的 Mars Session 来创建 "
"joblib Mars 后端。如果不指定任何参数，默认或者本地 Mars Session 将会被"
"使用。"

#: ../../source/user_guide/learn/joblib.rst:34
msgid ""
"A simple example is shown below, where we fit a SVM classifier with "
"randomized search. All you need is to replace the service endpoint in "
"``joblib.parallel_backend`` with your own service endpoint."
msgstr ""
"一个简单的例子如下。在该例子中，我们使用随机搜索来训练和优化一个 SVM "
"分类器。你只需要将代码中的 ``joblib.parallel_backend`` 替换成你自己的 "
"Mars 服务地址即可执行该代码。"

#: ../../source/user_guide/learn/joblib.rst:62
msgid ""
"Note that joblib can only be used with data small enough to be held "
"inside a single machine. For huge datasets, please use learning "
"algorithms implemented with Mars objects."
msgstr ""
"需要注意的是，joblib 只应当在小规模数据集上使用，这些数据应当能够存储在"
"单机内存中。对于大规模数据，建议使用 Mars learn 中针对 Mars 数据对象包装"
"的算法。"

