At Forge.AI, we develop capabilities for transforming unstructured streams of data into a structured format consumable by other AI systems. Tensorflow is one of the principal toolkits we use in developing and deploying our capabilities, such as hierarchical classification. This past March, I had the opportunity to attend TensorFlow Dev Summit 2018 at the Computer History Museum in Mountain View and represent the work we are doing at Forge.AI.
Suppose you’d like to classify individual documents at multiple levels of specificity. In addition, you’d also like to know whether a document contains multiple topics and with what confidence. For example, as I write this Google News is displaying an article titled Income Stocks With A Trump Tax Bonus. We may want to capture the main topics contained in the article along with an associated measure of our confidence that those topics are contained in the article. Such a classification might look something like the following