AI-Accelerated Product Development
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With this list, you will learn about the count-based way of constructing vector space models (VSMs) in NLP practices
Potential Use Cases
Figuring out co-occurrence of various words in corpuses or the topic model of a specific document
Who is This For ?
Python beginners to machine learning
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1. Vector Semantics
How are the count-based models represented within the matrix?
2. Improve Simple Co-Occurrence Counts
Are context words at different distances equally important? If not, how can we modify co-occurrence counts?
In language, word order is important; specifically, left and right contexts have different meanings. How can we distinguish between the left and right contexts?
3. Creating a sparse Document Term Matrix for Topic Modeling with LDA
How do you create a term-document model from scratch and apply one of the common-use applications?