Miscellaneous
Data Science
Data science encompasses data collection, cleaning, exploratory analysis, statistical modeling, machine learning, and visualization to derive actionable insights. It sits at the intersection of mathematics, computer science, and domain expertise.
Data scientists are central to AI development: they identify valuable data sources, engineer features, build and evaluate models, and translate analytical findings into business decisions. The distinction between data science and ML engineering has blurred as both involve model development and deployment.
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Related Terms
Core Concepts
Machine Learning
Getting computers to learn from data and improve at tasks without explicit programming.
Miscellaneous
Dataset
An organized collection of data examples prepared for training, evaluating, or testing AI models.
Miscellaneous
Training Data
The labeled or unlabeled dataset used to fit a model's parameters during the learning process.
Core Concepts
Big Data
Extremely large datasets that reveal patterns, trends, and associations through computational analysis.