Data Science Glossary
Browse 10 data science terms defined in plain English, from the cultural dictionary of computing.
10 Data Science Terms
- clustering
- An unsupervised machine learning technique that groups similar data points together without predefined labels. Common algorithms include k-means, DBSCAN, and...
- cohort analysis
- A technique that groups users by a shared characteristic (typically signup date) and tracks their behavior over time. Instead of looking at aggregate metrics...
- correlation
- A statistical measure (typically Pearson's r, ranging from -1 to +1) that quantifies the strength and direction of the linear relationship between two...
- dimensionality reduction
- A set of techniques (PCA, t-SNE, UMAP) that reduce the number of features in a dataset while preserving as much meaningful structure as possible. Essential...
- feature engineering
- The process of using domain knowledge to create, transform, or select input variables (features) that improve a machine learning model's predictive...
- Jupyter
- An open-source platform for interactive computing that lets users create notebook documents combining live code, equations, visualizations, and narrative text....
- NumPy
- The foundational Python library for numerical computing, providing support for large multi-dimensional arrays, matrices, and a vast collection of mathematical...
- pandas
- An open-source Python library providing high-performance, easy-to-use data structures (DataFrames and Series) and analysis tools. Built on top of NumPy, pandas...
- p-value
- The probability of obtaining results at least as extreme as the observed data, assuming the null hypothesis is true. A small p-value (typically below 0.05)...
- R
- A programming language and environment specifically designed for statistical computing and data visualization. R's comprehensive package ecosystem (CRAN) and...
Related Topics
- Python (3 terms in common)
- Statistics (3 terms in common)
- Machine Learning (3 terms in common)
- Visualization (2 terms in common)
- Analytics (2 terms in common)
- Experimentation (1 terms in common)
- Dataframes (1 terms in common)
- Modeling (1 terms in common)
- Notebooks (1 terms in common)
- Language (1 terms in common)
- Product (1 terms in common)
- Interactive (1 terms in common)
- Numerical Computing (1 terms in common)
- Unsupervised (1 terms in common)
- Retention (1 terms in common)