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Applied Machine Learning

ML: Decision-Making Lightsaber

In this era of big data, applied machine learning adds a new dimension of business intelligence for supply chain and operations teams. In an instant, ML-powered solutions can consider large amounts of data from a wide variety of sources, an effort that humans simply can’t match.

But it’s not just about the breadth of data it can consider. Machine learning can identify relationships between disparate data trends that we humans could never spot. And machine learning solutions can use real-time conditions to recommend decisions that give you the best chance of meeting specific business objectives. For decision makers, adding machine learning is like upgrading from a sword to a lightsaber.


Machine Learning Expertise

We’ve been providing insight to operations and supply chain teams since 2006. To do so, we are experts at finding and integrating the right tools to solve a client’s specific business problem. Our focus in applied machine learning includes:

  • Deep learning and neural networks
  • supervised vs. unsupervised machine learning
  • Logistic and linear regression
  • Linear discriminant analysis
  • Classification and regression trees
  • Naive Bayes
  •  K-means clustering and K-nearest neighbors (KNN)
  • Learning vector quantization
  • Support vector machines
  • Bagging and random forests
  • Boosting and AdaBoost
  • Predictive analytics
  • Cloud-based machine learning
  • Machine learning frameworks