tomotopy is a Python extension of tomoto (Topic Modeling Tool) which is a Gibbs-sampling based topic model library written in C++. It utilizes a vectorization of modern CPUs for maximizing speed. The current version of tomoto supports several major topic models including
In natural language understanding, there is a hierarchy of lenses through which we can extract meaning - from words to sentences to paragraphs to documents. At the document level, one of the most useful ways to understand text is by analyzing its topics.
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After graduating from the five-minute wiki to real-life applications, Django programmers can easily create confusing, hard-to-maintain, or inefficient model classes. Learn how to avoid common querying mistakes, use model managers to encapsulate complex queries, and take advantage of the powerful new aggregation features available in Django V1.1.
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