<h1>Vowpal Wabbit</h1>
<p>VW is a command-line machine learning software that is designed to efficiently work with large amounts of data, that is not limited by RAM. It supports online learning. The software gained popularity as a tool used by multiple users on Kaggle competitions.</p>
<p>As described on its <a href="https://github.com/JohnLangford/vowpal_wabbit" rel="nofollow noreferrer">github page</a>:</p>
<blockquote>
<p>Vowpal Wabbit is a machine learning system which pushes the frontier
of machine learning with techniques such as online, hashing,
allreduce, reductions, learning2search, active, and interactive
learning. <a href="https://vowpalwabbit.org/" rel="nofollow noreferrer">https://vowpalwabbit.org/</a></p>
</blockquote>
<p>Pretty detailed documentation with code examples can be found on the <a href="https://github.com/JohnLangford/vowpal_wabbit/wiki" rel="nofollow noreferrer">github Wiki page</a> of the project. Video lecutres by John Langford, creator of VW, giving introductory tutorials can be found on YouTube <a href="https://www.youtube.com/watch?v=N-x86zHUDaI" rel="nofollow noreferrer">here</a> and <a href="https://www.youtube.com/watch?v=HEob9cRkpDk" rel="nofollow noreferrer">here</a>. There is also arXived paper <a href="https://arxiv.org/abs/1110.4198" rel="nofollow noreferrer">&quot;A Reliable Effective Terascale Linear Learning System&quot;</a> by Agarwal et al describing theoretical basis of the software.</p>
