A lot of the recent advancements in AI are based upon deep learning technology.

While there are many classic machine learning algorithms based around statistical algorithms, deep learning works by mimicking the human brain.

Or, more specifically, around how neuroscientists believed how the human brain worked in the 80s.

Models built on deep learning frameworks can do astonishing things when finding and creating patters from data.

Here’s a great primer on the most basic type of deep learning structure: the feed forward neural network.

Feedforward neural networks were among the first and most successful learning algorithms. They are also called deep networks, multi-layer perceptron (MLP), or simply neural networks. As data travels through the network’s artificial mesh, each layer processes an aspect of the data, filters outliers, spots familiar entities and produces the final output.

In this video, Siraj Raval demonstrates how to build a CyberSecurity startup around a demo app called DharmaSecurity, a fraud detection tool for businesses.

The way it works is that once signed up, a business will paste a code snippet into their website, and then they’ll get access to a dashboard that tells them how many fraudulent accounts they have.

TensorFlow is already one of the most popular tools for creating deep learning models.

Google this week introduced Neural Structured Learning (NSL) to make this tool even better.

Here’s why, NSL is a big deal.

Neural Structured Learning in TensorFlow is an easy-to-use framework for training deep neural networks by leveraging structured signals along with feature inputs. This learning paradigm implements Neural Graph Learning in order to train neural networks using graphs and structured data. As the researchers mention, the graphs can come from multiple sources such as knowledge graphs, medical records, genomic data or multimodal relations. Moreover, this framework also generalises to adversarial learning.

Here’s a great blog post on how to build out a Knowledge Mining solution on Azure with Azure Search and Cognitive Services.

Recently, Uche Adegbite and I had the opportunity to discuss Knowledge Mining with Azure Search at the Microsoft Azure Government DC Meetup . In our presentation we demonstrated how to use Cognitive Search to take your knowledge discovery capabilities to the next level. This brief post is a follow-up […]