As machine learning gains traction in digital businesses, technical professionals must explore and embrace it as a tool for creating operational efficiencies. This primer discusses the benefits and pitfalls of machine learning, the requirements of its architecture, and how to get started.
- What Is Machine Learning?
- What Business Trends and Benefits Are Driving Machine Learning?
- Examples of How Machine Learning Can Deliver Value to Organizations
- Machine Learning Can Also Provide Process Benefits for IT Organizations
- Business Strengths and Challenges of Machine Learning
- How Should IT Prepare for Machine Learning?
- Learn the Stages of the Machine Learning Process
- Understand the Model Development Life Cycle Needed for Machine Learning
- Understand the Basic Architecture Needed for Machine Learning
- A Comprehensive End-to-End Architecture
- Understand What Skills Will Be Needed for Machine Learning
- Steps to Get Started With Machine Learning
- Learn About and Experiment With ML Concepts and Technology
- Work Closely With Data Science Teams and Business Users to Identify a Use Case
- Build a Use Case in the Cloud
- Iteratively Expand Your ML Platform and Services Over Time
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