Identify Complex Data Relationships
Our deep learning capabilities are discovering complex features and relationships in high-dimensional data and informing both decision systems and design structures.
These models are composed of multiple processing layers designed to learn about the feature abstraction in the data. And, the paradigms have helped accomplish complicated tasks, achieving major breakthroughs in a number of domains.
Business challenges come in all shapes and sizes. Tackling them requires a range of capabilities. Cognizant’s AI is structured around three distinct capability profiles, helping you to explain, predict and respond across the business ecosystem.
Make smarter decisions faster
Companies that make the right decisions
at the right time succeed.
Businesses succeed or fail by the speed and quality of their decisions. Whether the goal is revenue, profitability, a competitive edge or all of the above, the best decisions are the ones informed by data and AI.
How will artificial intelligence affect transportation?
Technological advancements have helped the transportation sector progress in its journey of innovation and evolution.
Leveraging AI in transportation helps the sector increase passenger safety, reduce traffic congestion and accidents, lessen carbon emissions, and also minimize the overall financial expenses
Machine learning consulting and development
Predict results and prevent asset failures with customized data science and machine learning solutions.
Discuss your deep thoughts or intricate issues with our machine learning experts, who can provide constant consultation. We automate business and optimize processes by implementing intelligent ML solutions Machine learning methods
Computer vision, Deep learning, Feature extraction, Knowledge representation, Learning to classify, Natural language generation, Natural language processing, Neural network, Reinforcement learning, Semi-supervised learning, supervised learning, Unsupervised learning
Machine learning techniques.
Anomaly detection, automatic coders, Bayesian statistics, classification, cluster calculation, decision trees, deep belief network, generative. Linear regression, logistic regression, principal component analysis, gradient increase.