Although ANNs have been around for decades, new recent advances in technology allow ANN algorithms to become more sophisticated with the use of Deep Learning.
Deep Learning has proved it can outperform any other algorithm when it comes to complex problems such as classification, natural language processing, speech recognition and predictions.
The special characteristic for DNN is the “learning through training” modality, resembling the capacity of the brain to learn, assimilate and recall this knowledge in anticipation of a future event.
Via trained learning, the network self-adapts and changes its structural characteristics; this is based on the information that flows through the network neurons.
Our goal is to develop a deep neural network with your organization's data to estimate the chance of success of any future action.
We will use your databases to load, train, test and evaluate our models. The combination of all those data, will help our algorithm to understand human actions in a better way.