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

no edit summary
No edit summary
No edit summary
Line 136: Line 136:
=Snap ML= <!--T:34-->
=Snap ML= <!--T:34-->
[https://snapml.readthedocs.io/en/latest/ Snap ML] is a closed-source Machine Learning library being developed by IBM. <code>Snap ML</code> currently supports a number of classical machine learning models and scales gracefully to data sets with billions of examples and/or features. It offers distributed training, GPU acceleration and supports sparse data structures. It features an API very similar to <code>scikit-learn</code> and can be used as a replacement for that library when dealing with massive datasets.
[https://snapml.readthedocs.io/en/latest/ Snap ML] is a closed-source Machine Learning library being developed by IBM. <code>Snap ML</code> currently supports a number of classical machine learning models and scales gracefully to data sets with billions of examples and/or features. It offers distributed training, GPU acceleration and supports sparse data structures. It features an API very similar to <code>scikit-learn</code> and can be used as a replacement for that library when dealing with massive datasets.
== Installation ==
===Latest available wheels===
To see the latest version of PyTorch that we have built:
{{Command|avail_wheels "snapml"}}
For more information, see [[Python#Available_wheels |Available wheels]].
===Installing the Compute Canada wheel===
The preferred option is to install it using the Python [https://pythonwheels.com/ wheel] as follows:
:1. Load a Python [[Utiliser_des_modules/en#Sub-command_load|module]], thus <tt>module load python</tt>
:2. Create and start a [[Python#Creating_and_using_a_virtual_environment|virtual environment]].
:3. Install PyTorch in the virtual environment with <code>pip install</code>.
:{{Command|prompt=(venv) [name@server ~]|pip install --no-index snapml }}


==Multithreading== <!--T:35-->
==Multithreading== <!--T:35-->
cc_staff
282

edits