Artificial Intelligence (AI) is a main part of computer science which tries to develop intelligent computers or machines that are able to replicate at least some aspects of human intelligence, such as reasoning, planning, learning, problem solving and even natural language communication.

At Eris Innovation we are extremely passionate about providing and offering comprehensive AI-based solutions to private and public businesses globally.

Machine Learning

Machine Learning is a crucial part of Artificial Intelligence that makes computers and machines to be able to learn without being explicitly programmed. Machine Learning as a novel technology in the field of computer science refers to the process of designing and developing complex models and algorithms that themselves can learn from data and adjust the system actions accordingly. We are highly capable of developing and devising cutting-edge Machine Learning-based methods and algorithms with the both supervised and unsupervised approaches.

Deep Learning

Deep learning is a set of algorithms in machine learning that attempt to learn in multiple layers of non-linear transformations. Deep structured learning has surpassed most of conventional methods in many learning tasks such as voice or image recognition. Thanks to our profound and extensive mathematical knowledge and also our full access to high performance computational facilities, at Eris Innovation we are developing several Deep Learning software programs to mimic the neocortex's activities by huge arrays of virtual neurons in an artificial neural network to provide effective and practical solutions from personalized product engineering to adaptive algorithmic trading and investment.

Pattern Recognition

Pattern Recognition is the science of analysis, extraction and identification of patterns in data. Automatic machine recognition is a key ability of computers to be intelligent enough for recognizing time trends within datasets or visual patterns in an image for example. At Eris Innovation we aim to make the process of studying and detection of patterns explicit, such that the computer machines would be able to recognize specific behaviors or data classes automatically to support and develop smart decision making modules.