Machine Learning. Such a cool name, and such a powerful technology. But there’s a lot of work required on your part if you want to successfully apply it to your problems. Beware of these 5…
If you’ve built a cognitive system, you know that it requires a lot of training to reach peak performance. (For details, read Why does machine learning require so much data?) How much training data do you…
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…
Everywhere I look I see people trying to solve problems with machine learning. It’s an exciting time to be a cognitive developer! One area I see these people struggling in is gathering sufficient training data…
I recently completed a seven-post series on the IBM Watson Developer Blog about Cognitive System Testing. These posts reflect some hard-learned lessons from the past few years. Cognitive systems present some interesting challenges for testing-minded…
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…