At Talla, we build products that help people find and make use of an organization’s internal knowledge. While we've already implemented technology for enterprises with models that are successfully in production, we continuously experiment with different data and methods that have less certain outcomes. In my talk at the Machine Learning Conference, which you can watch below, I shared what happened when we experimented with using chat data for issue detection and matching.
The recent boom in machine learning has seen a tremendous rise in the popularity and popularization of complex machine learning methods. Techniques previously relegated to the annals of academic discourse have become common topics of discussion in some tech circles. Terms such as convolutional neural networks, variational autoencoders, and even Deep Q-learning have now become important to many people who previously could hardly be troubled to care about the latest fads in machine learning.
Topics: machine learning
This post is by Daniel Shank, a Senior Data Scientist at Talla. He recently gave a talk at The Machine Learning Conference in San Francisco on Neural Turing Machines. A recording and full transcript for his talk can be found below.