Machine Learning Playbook

At this point on the timeline for machine learning solutions, most opportunities for ML in an organization still go for naught.

 

Perhaps the organization doesn’t fully understand the technology and how and where to apply it. Or prior ML solutions were poorly developed and don’t perform as intended.

 

Or, ML projects just aren’t a priority — although they should be, given the efficiency and intelligence ML brings to an organization’s data and workflows.

ML Playbook Download

Download the Machine Learning Playbook
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For engineers, managers, and domain experts, our Machine Learning Playbook provides a framework to identify best fit opportunities for ML throughout your organization.

It’s also a complete guide to help you navigate the process of planning and implementing ML projects successfully, with best practices for:

 

  • Process Mapping

  • Data Identification and Validation

  • Data Aggregation

  • Data Exploration, Cleaning and Engineering

  • Data Labeling

  • ML Algorithm Research

  • ML Training and Tuning

  • ML Deployment

  • Model Improvement and Sustainability

 

If ML is on your organization’s roadmap, we’re here to help. Consider this Machine Learning Playbook the starting point.