The good news for non-developers is that it’s possible to build a predictive model without machine learning or coding skills. What is a predictive model? Predictive modeling, also referred to as predictive analytics, is the process that uses a historical dataset to build a mathematical solution with the purpose to predict outcomes from new data. […]
In this interview to La Tribune (Parole d’Experts), Mr. Gazikian talks about data iceberg, differences between Small Data and Big Data, machine learning and why TADA is different from other predictive modeling platforms. Start using TADA now or learn more about our predictive modeling software for Small Data.
What is the next phase of your data strategy? In recent years, data strategy has been focused towards analysis of huge data sets in domains where data are easy to collect. On the other hand, there are domains where generating each data point is very time consuming or expensive, as a result, they deal with […]
MyDataModels laureate of the 21st edition of the i-Lab competition organized by the Ministère de l’Enseignement supérieur, de la Recherche et de l’Innovation & bpifrance. During the 21st edition of the i-Lab competition, the national jury of experts chose MyDataModels on its GPITISS project – Genetic ProgrammIng for TIme SerieS, an ambitious project carried out […]
MyDataModels CEO Simon Gazikian explains at the 2018 European Society of Cardiology Congress
Table of Contents Introduction and Forward The Purpose of Data Pre-Processing Human Interpretation Algorithmic Imposed Constraints/Limitations Considerations when Employing Transformative Pre-Processing Imparting attributes of sample composition upon individual records Additional considerations Assessment of predictive models based on transformed data Considerations with respect to MyDataModels ZGP engine Introduction and Forward This document will describe a number […]