Machine learning


Machine learning (ML) comes under Artificial Intelligence that is a mathematical model build based on sample data known as “training data”. ML systems uses cognitive learning methods to make predictions without being explicitly writing a computer program to do so. In other words, those machines are well known to grow better with experience.

Predictive modeling, on the other hand, is a mathematical technique which uses statistics for prediction. It aims to work upon the provided information to reach an end conclusion after an event has been triggered. So, the end outcome of this model is constrained to program defined outcomes.

ML and Predictive Analytics both serve the same purpose. NYGCI connects your data from business intelligence tools to ML technologies to create a devise that generates complex algorithms and models which lend themselves to a prediction. It is widely used by customers to make decisions and provide results to uncover the hidden growth opportunities by making use of historical learning.

A wide range of advantages exist incorporating machine learning and predictive analytics. Artificial intelligence Operations (AIOps) is the application of artificial intelligence (AI) to improve IT operations efficiency. NYGCI’s AIOps framework uses big data, data analytics, and machine learning capabilities to proactively respond to production hiccups or outages, with a lot less effort.

Our machine learning analytics services help enterprises to design strategies that turns their business data into a benefits and competitive advantage. NYGCI uses one-of-a-kind associative analytics engine, sophisticated AI, and high-performance cloud platform that you can empower everyone in your organization to make better decisions daily, creating a truly data-driven enterprise. Our analytics services is backed by our business intelligence experts who have unique approach to develop solution that analyzes each piece of information before taking any critical business decision.

NYGCI’s founder has been in Artificial intelligence since 2002 (before the company was formed in 2007) and our team holds advanced artificial intelligence skills. They are experienced to apply state-of-the-art techniques, tools, and technologies.