A Dictionary of Common Data Science Terms: Essential Statistics, Machine Learning, AI, and Predictive Analytics Definitions for Beginners and Students
Data science brings together statistics, machine learning, programming, artificial intelligence, and predictive analytics. Understanding the terminology behind these disciplines is an important step toward learning how data is collected, analyzed, modeled, and used to solve real-world problems.
A Dictionary of Common Data Science Terms is a practical reference featuring 158 carefully selected terms used in modern data science.
Written for students, beginners, career changers, aspiring data professionals, and IT professionals, this dictionary explains important technical concepts in clear, accessible language without unnecessary academic complexity.
WHAT YOU WILL FIND INSIDE
158 essential terms covering the foundations and practical applications of data science.
Clear, concise definitions designed to make technical vocabulary easier to understand.
Helpful cross-references connecting related terms and concepts.
Alphabetical organization for quick lookup, study, and everyday reference.
EXPLORE IMPORTANT DATA SCIENCE TOPICS
The dictionary covers a broad selection of frequently encountered terminology, including:
Data collection, preparation, cleaning, and transformation
Descriptive statistics, probability, and hypothesis testing
Exploratory data analysis and visualization
Supervised and unsupervised machine learning
Classification, regression, and clustering
Feature engineering and predictive modeling
Model training, validation, and performance evaluation
Neural networks and artificial intelligence
Python, NumPy, pandas, scikit-learn, and SQL
Forecasting, time series, and predictive analytics
Model deployment, monitoring, and MLOps
WHO THIS BOOK IS FOR
Whether you are beginning a data science course, preparing for a technical interview, exploring a career in analytics, studying machine learning, or expanding your professional vocabulary, this dictionary offers a convenient reference to the terminology you are most likely to encounter.
Unlike a comprehensive academic textbook, this book focuses on the practical meaning of commonly used terms, making it suitable for quick consultation and independent study.
Build your data science vocabulary. Understand important concepts. Learn the language of modern data-driven technology.
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