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Blogs Page 4

  • Using Transaction Data for Optimal Customer Segmentation Analysis

    Using Transaction Data for Optimal Customer Segmentation Analysis

    We examine how to apply machine learning to segment based on transaction data and transform those clusters into customer segments.

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  • Root Cause Analytics of Telemetry Failures

    Root Cause Analytics of Telemetry Failures

    Root cause and diagnostic analytics is a great approach for identifying computer failures.

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  • Deep Learning Review from a Mosaic Data Scientist

    Deep Learning Review from a Mosaic Data Scientist

    One of our data scientists takes an intensive review of deep learning applications, exploring how deep learning is being applied in the world today and what it means at Mosaic.

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  • Aircraft Trajectory Optimizer

    Aircraft Trajectory Optimizer

    Optimizing how airplanes take off is a perfect use case for fusing IoT and predictive analytics.

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  • Aircraft Performance Model IoT Data Mining

    Aircraft Performance Model IoT Data Mining

    We examine how to apply ML & AI for the IoT use case of mining for aircraft performance insights.

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  • Tips for Customer Propensity Modeling

    Tips for Customer Propensity Modeling

    Propensity modeling is a powerful ML technique for solving multiple marketing analytics use cases.

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  • Human Decision Making in Machine Learning Deployment for Resume Matching

    Human Decision Making in Machine Learning Deployment for Resume Matching

    Utilizing AI techniques like NLP is a great way to reduce the time it takes to find optimal candidates for job openings.

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  • Human Decision Making in Machine Learning Deployment for Air Traffic Flow Management

    Human Decision Making in Machine Learning Deployment for Air Traffic Flow Management

    Being able to accept machine learning outputs in the decision making process is critically important, especially in Air Traffic decisions.

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  • Filling Predictive Modeling Gaps with Anomaly Detection

    Filling Predictive Modeling Gaps with Anomaly Detection

    Anomaly detection is a great technique to use in supervised machine learning and AI applications.

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  • Finding External Data Sources: Data is Everywhere!

    Finding External Data Sources: Data is Everywhere!

    Sometimes in ML & AI development, a data scientist will need to go and find external data sources to complement the modeling efforts.

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