Advancements in machine learning (ML) are driving breakthroughs in AI, finally delivering on their promises to everyday business users.
There is a catch, though. Getting the right data, at the right time, to the correct models is crucial to the newfound abilities of ML and AutoML. Use this TDWI Checklist report to ensure you cover all the business and technical requirements for preparing data for ML and related practices in AI and predictive analytics.
Read this report to:
- Understand the ML lifecycles and how data requirements vary across lifecycle stages
- Learn how to leverage a modern cloud data warehouse and a data lake to build your ML models
- Select your first steps in ML-driven AI and predictive analytics based on business needs and sensible project planning