Daines Analytics is the developer of the CODA (Contract Opportunities Decision Analytics) suite of data solutions. We designed CODA to help procurement/contracting officers in large government organizations find small/medium businesses who can offer goods/services that are an excellent match to the needs of the contracting organizations. By leveraging predictive analytics, automated infrastructure, and process design, CODA seeks to maximize the synergies while minimizing the risks of the contracting opportunities between two or more organizations.
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Daines Analytics
Predictive Analytics | Automated Infrastructure | Process Design
Analytics Solutions for Building Tomorrow’s Digital Capabilities
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David Lowe
Chief Technology Officer, Daines AnalyticsAnalytics Journal
Template Credit: Adapted from a template made available by Dr. Jason Brownlee of Machine Learning Mastery. SUMMARY: The purpose of this project is to construct a predictive model using various machine learning algorithms and to document the end-to-end steps using a template. The Allstate Claims Severity dataset is a regression situation where we are trying… Read More
Continue ReadingRegression Model for Allstate Claims Severity Using Python Take 2
Template Credit: Adapted from a template made available by Dr. Jason Brownlee of Machine Learning Mastery. SUMMARY: The purpose of this project is to construct a predictive model using various machine learning algorithms and to document the end-to-end steps using a template. The Allstate Claims Severity dataset is a regression situation where we are trying… Read More
Continue ReadingRegression Model for Allstate Claims Severity Using Python Take 1
Template Credit: Adapted from a template made available by Dr. Jason Brownlee of Machine Learning Mastery. SUMMARY: The purpose of this project is to construct a predictive model using various machine learning algorithms and to document the end-to-end steps using a template. The Allstate Claims Severity dataset is a regression situation where we are trying… Read More
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