In building a cognitive model it can be difficult to know when it’s accurate enough. (You are measuring your daily performance, right?) We know that cognitive performance often involves making a tradeoff between the competing…
Introduction In my past posts, I showed both how to create a simple NLP model with rules and machine learning, and how to improve those same rules and machine learning NLP models. In this post…
Introduction In my last post, I introduced a simple Natural Language Processing (NLP) problem: extracting mentions of programming languages from the Wikipedia article on programming languages, using both a rules-based technique and a machine learning…
Introduction In this cognitive area, many people are interested in using natural language processing (NLP) to extract insights from their large collections of unstructured text. There are two main approaches to natural language processing: rules-based…
In part 1 of Training a personal chatbot with Watson Developer Cloud APIs I gave an intro to text classification and how you could use it to create a chat bot that screened your incoming questions…
The Watson Developer Cloud APIs are intended to give you building blocks for building your own applications with the cognitive capabilities of Watson. There’s been a lot of press on combining Watson and Slack, and…
I’ve been building a set of natural language processing (NLP) annotators and have frequently been asked about my confidence in the results. This is an interesting question with a simple answer and a more complex…