Large Scale Machine Learning (Big Data): Difference between revisions

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All estimators in <code>Snap ML</code> support thread parallelism, which can be controlled via the <code>n_jobs</code> parameter. Setting this parameter to the number of cores available in your job will typically deliver a good speed-up relative to the <code>scikit-learn</code> implementation of the same estimator. The following is a performance comparison of <code>Ridge</code> between <code>scikit-learn</code> and <code>Snap ML</code>.
All estimators in Snap ML support thread parallelism, which can be controlled via the <code>n_jobs</code> parameter. Setting this parameter to the number of cores available in your job will typically deliver a good speedup relative to the scikit-learn implementation of the same estimator. The following is a performance comparison of <code>Ridge</code> between scikit-learn and Snap ML.


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