We exploited our know-how and expertise in Artificial Intelligence by developing a platform performing Deep Learning algorithms to train models and provide predictions
It is a platform designed to be used and managed by non-expert users.
It is built on application layers that are horizontally scalable and able to recognize patterns by analyzing huge amount of data.
It can find out by itself the best model to be applied to data under analysis, while user doesn't need to make any choice or setting.
It is not focused on nor targeted to only one specific domain: it is able to analyze and manage any kind of data, regardless of the domain the data belong to.
MODEL SELF-IMPROVEMENT AND CLEANING
It embeds a model self-improving capability, for the sake of a feature that allows to add authomatically new data and to clear the data-set from fake data.
Neural Networks, Random Forest, SVM and Logistic Regression, Probabilistic Classifier, Linear regression, Isotonic regression, Survival regression, Gradient boost regressor, LSTM Neural Networks, IsolationForest, LGBRegressor, LGBClassifier.