Top Considerations for Building A Production-ready AI/ML Environment

AI/ML employs data to deliver business insight, automate tasks, and advance system capabilities.  Building AI/ML into existing software applications can help to increase revenue, reduce overhead costs and optimize existing business services. However, deploying AI/ML in production is an iterative process that extends beyond simply creating AI/ML models.

This eBook covers the steps required to successfully build a production-ready AI/ML environment process from:
● Setting business goals for your AI/ML initiative
● Gathering and preparing data required for your AI/ML initiative.
● Developing machine learning/deep learning  models
● Deploying ML/DL models in your application development process.
● Implementing intelligent, ML/DL-powered applications and inferencing.
● Monitoring and managing models for accuracy over time.

Top considerations for building a
production-ready AI/ML environment