Textual analysis
Modern applications use Natural Language Processing (NLP) for several purposes, such as text translation, document classifications, web search, Named Entity Recognition (NER), and many others.
AWS offers a suite of algorithms for most NLP use cases. In the next few subsections, you will have a look at these built-in algorithms for textual analysis.
BlazingText algorithm
BlazingText does two different types of tasks: text classification, which is a supervised learning approach that extends the fastText text classifier, and Word2Vec, which is an unsupervised learning algorithm.
BlazingText’s implementations of these two algorithms are optimized to run on large datasets. For example, you can train a model on top of billions of words in a few minutes.
This scalability aspect of BlazingText is possible due to the following:
- Its ability to use multi-core CPUs and a single GPU to accelerate text classification
- Its ability to use multi-core...
