Regular expressions are a powerful method for finding specific patterns in text. The syntax of regular expressions is intimidating, but once you've solved a few pattern-recognition problems with regex, you'll never go back to your old methods.
Regular expressions are a powerful method for finding specific patterns in text. The syntax of regular expressions is intimidating, but once you've solved a few pattern-recognition problems with regex, you'll never go back to your old methods.
Amidst the growing popularity of modern machine learning and deep learning techniques, one of the biggest challenges is the ability to obtain large amounts of training data suitable for your use case. This post discusses how the analytical approach for Named Entity Recognition (NER) can help.
Deep learning has taken off because organizations of all sizes are capturing a greater variety of data and can mine bigger data, including unstructured data. It’s not just large companies like Amazon, SAS and Google that have access to big data. It’s everywhere. Deep learning needs big data, and now