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Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Our Machine learning methods are
Instance-based algorithm. K-nearest neighbors algorithm (KNN) Learning vector quantization (LVQ).
Regression analysis. Logistic regression. Ordinary least squares regression (OLSR).
Regularization algorithm. Ridge regression.
Classifiers. Probabilistic classifier.
EXPERTS IN OUR TEAM
Machine Learning Engineer
Machine Learning Solutions Architect
We have mastered all aspects of the machine learning lifecycle, from analyzing and building models to implementing the business processes and infrastructure to bring machine learning solutions to production.
WHAT CAN OUR EXPERTS DO FOR YOU?
Our team has mastered all aspects of the machine learning lifecycle, from analyzing and building models to implementing the business processes and infrastructure to bring machine learning solutions to production.
Our Machine Learning partnership aims to support clients in the development and implementation of Machine Learning innovations in the field of automating choice processes in business operations.
A challenge that larger organizations often face is focusing on the service provided on the personal needs of customers. It takes a lot of human capacity to analyze and act on the amount of information available for each customer. Machine Learning solves this problem by automating the processing and interpretation of large amounts of customer information. This leads to useful insights at the customer level. With the help of these automated insights, the service can be tailored to the needs of the customer.
In addition, Machine Learning can also help optimize business processes that do not involve customer data. Algorithms offer solutions for the automated interpretation of images, sensor data and/or other data in which patterns and regularities can be recognized. In this way, it is possible to make tasks that require cognitive capacity more scalable by means of smart automation.