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 Crop Mapping in Canada dataset is a multi-class classification situation where we… Read More
Continue ReadingMulti-Class Classification Model for Crop Mapping in Canada Using Scikit-Learn 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 Crop Mapping in Canada dataset is a multi-class classification situation where we… Read More
Continue ReadingUpdated Scikit-Learn Machine Learning Templates v14 for Python
As I work on practicing and solving machine learning (ML) problems, I find myself repeating a set of steps and activities repeatedly. Thanks to Dr. Jason Brownlee’s suggestions on creating a machine learning template, I have pulled together a set of project templates that I use to experiment with modeling ML problems using Python and… Read More
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