A method of data analysis that automates the analytical model building based on the notion that systems can learn from prescriptive data,
identify array of data and make a sequence of decisions with minuscule human interaction.
Machine learning, deep learning, cognitive computing and natural languages are emerging technologies that drives business decision
making for some of the most innovative organizations today. They are used to target and personalize product marketing campaigns,
genomics and for innovative product features such as the self-driving vehicle. While this phenomenon has been around for quite some time now,
technological improvements have created a platform for such analysis to automatically apply complex mathematical calculations to big data
repetitively and at a much faster rate.
Our engineers and data scientists have product lifecycle (requirements and design through implementation deployment) experience with machine learning
and deep learning systems. We have expertise geospatial modeling and maritime analytics, predicting faults and challenges in 4G-LTE networks
and developing predictive models for field service operations. Considering the perpetual evolution of deep learning, our data scientists are
abreast with the most recent methods, statistical tools and IoT technologies to deliver excellence.
Our daily interaction with machine learning goes beyond the traditional use with organization’s leveraging innovations to determine their competitive advantage.
Today machine learning applications can perform a series of impactful actions such as:
The self-driving car
Delivery on smartphones or tables of personalized online
recommendation offers such as those from Amazon and Netflix.
Product marketing strategies that determine customer
opinion on the various social networks