Predictive Analytics

Using data to predict the future

Turn your data into competitive advantage

Advanced analytics is a strategic and integral tool for business. Using algorithms that detect patterns and make predictions based on historical data and associated outcomes, businesses can make more informed decisions to drive results.

  • Improved business efficiencies
  • Higher productivity
  • Enhanced user engagement
  • Improved profitability

Our services are based on a fine-tuned approach, methodology, solution accelerators, and processes. We can help you implement or optimize predictive analytics for your organization.

Supervised Learning

To predict behavior based on the relationship between inputs to outputs. Supervised learning is helpful in such areas as fraud detection, market and customer segmentation, pattern or face recognition, image classification, market forecasting, and advertising popularity predictions. Algorithms: Linear Regression, Decision Tree, Random Forest, Logistic Regression.

Unsupervised Learning

To find patterns and classify the data without an explicit output variable. Unsupervised learning is helpful in recommendation systems, customer segmentation, spam filtering, news classification, social network analysis, search result grouping, image segmentation, anomaly detection, Big Data visualization, feature elicitation, and email classification. Algorithms: K-Means Clustering, Hierarchical Clustering, Gaussian Mixture Model.

Reinforced Learning

To perform a task by maximizing the rewards received. Reinforced learning can be helpful, for example, in optimizing pricing systems, optimizing trading strategies, and load balancing. Algorithms: Markov Decision Processes, Temporal Difference, Policy Gradient, Value Function, Q-Learning, SARSA.

Love working with leading edge technologies?