Even with a powerful machine learning solution like ALiX™, which can provide reliable and repeatable results, the ability of artificial intelligence to make effective predictions can depend on the quality of the training data and the structure of the neural network.
The neural network is a machine with a large number of parameters, and it computes an output when presented with an input. During the training process, the errors between the computed outputs and the training labels are measured. The goal of training the network is to find the optimal set of parameters for the neural network which causes the errors to be minimized.
Neural networks can have a complicated structure, and finding a good structure can sometimes be a challenging task. So can the process of creating quality training data. With our consulting services, fueled by the power of ALiX™, we can help you maximize the predictive power of your artificial intelligence.