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Highly accurate, prescriptive, predictive algorithms help customers anticipate breakdowns so they can improve operations and avoid equipment downtime.
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As the field of data science continues to grow beyond the world of researchers and statisticians, it is important for our team to arm developers with a wide range of programming languages.
Mark Hall is responsible for developing machine-intelligence solutions at Hitachi Vantara Labs. An original core developer of Weka machine-learning software, he has 15 years of experience in academic research in computer science, and publishes extensively in machine-learning conferences and journals.
Monitor, evaluate, compare and rebuild predictive models to enable greater algorithmic transparency and improved business outcomes.
Maximize model accuracy while in production, choose from a broad selection of evaluation statistics to identify degraded models, and use rich visualizations and reports to analyze model performance and uncover inadequacies.
Weka is a collection of machine-learning algorithms that can either be applied directly to a data set or called from your own Java code. Weka contains tools for data preprocessing, classification, regression, clustering, association rules and visualization. It is also well-suited for developing new machine-learning schemes and building predictive models. Pentaho supports Weka with a data-scoring tool and forecasting for PDI to create predictions on incoming data.
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