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Finding patterns in data to derive information.
By Uche Ogbuji | Last updated September 19, 2018
As artificial intelligence and cognitive computing have gained interest in recent years, a lot of the attention has been on varieties of classifier systems. Classifier systems look for patterns to establish a given probability that a thing is of a certain type. Simple rules and actions can then be run based on this classification. To understand how generative techniques can take AI to the next level, it is important to understand their basics. The classic area of interest is still one of the most interesting: natural language. This series explores letter correlation and simple language statistics for AI, word analysis and N-grams in a variety of practical applications, and using Markov Chains to generate language from letter correlation matrices and N-grams.
To understand how generative techniques can take AI to the next level, it is important to understand their basics. The…
Build on the concept of N-grams of sequential letters to look at N-grams of words, and the statistics that can…
Now that you have learned how to compile statistics of letter correlation and word correlation in model natural language text,…
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