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"Machine learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions" (TechEmergence).
"Within the field of data analytics, machine learning is a method used to devise complex models and algorithms that lend themselves to prediction; in commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to 'produce reliable, repeatable decisions and results' and uncover 'hidden insights' through learning from historical relationships and trends in the data" (Wikipedia).
"The processes involved in machine learning are similar to that of data mining and predictive modeling. Both require searching through data to look for patterns and adjusting program actions accordingly" (TechTarget).
More from the data glossary
A definitive guide to data definitions and trends, from the team at Stitch.
- Analytics
- Big data
- Business intelligence (BI)
- Common table expression
- Data analytics
- Data architecture
- Data engineering
- Data enrichment
- Data exploration
- Data ingestion
- Data integration
- Data lake
- Data migration
- Data mining
- Data modeling
- Data pipeline
- Data preparation
- Data science
- Data visualization
- Data warehouse
- Data Wrangling: Definition and Examples
- Database
- Deduplication
- ELT
- ESB - What is an Enterprise Service Bus?
- ETL
- ETL pipeline
- Information lifecycle management (ILM)
- Machine learning
- Master data management (MDM)
- SaaS
- Service-oriented architecture (SOA)
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