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The Automation and Optimization of

Advanced Analytics Based on Machine Learning

Here’s how it works: Machine learning algorithms consume and process large volumes of data to learn complex patterns about people, business processes, transactions, events, and so on. This intelligence is then incorporated into a predictive model. Comparisons to the model can reveal whether an entity is operating within acceptable parameters or is an anomaly.

Machine learning is being used today to solve well-bounded tasks such as classification and clustering. Note that a machine learning algorithm learns from so-called training data during development; it also learns continuously from real-world data during deployment so the algorithm can improve its model with experience.

This report, written by TDWI and sponsored by Qubole, will drill into the data, tool, and platform requirements for machine learning with a focus on automating and optimizing ML’s development environment, production systems, voracious appetite for data, and actionable output.

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