Python for ML Glossary

Python language, NumPy, pandas, Matplotlib, and scikit-learn vocabulary for ML practitioners

Python - High-level, dynamically typed language that is the default for ML and data science.
Variable - A name that refers to a value in memory - Python is dynamically typed.
Data Type - The kind of value a variable holds: int, float, str, bool, list, dict, etc.
String - An immutable sequence of Unicode characters for any text.
Boolean - A type with two values, True and False, used for conditions and flags.
List - An ordered, mutable sequence indexed by integer position from 0.
Dictionary - A mutable key-value store with average O(1) lookup.
Tuple - An ordered, immutable sequence - like a list but cannot be changed.
For Loop - A loop that iterates over each item of an iterable.
if / else - Run different code branches based on whether a condition is True or False.
Function - A reusable named block of code defined with def, taking inputs and returning a value.
Module - A single Python file (or package) loaded with import to reuse code.
Package - A distributable bundle of one or more modules, installed via pip from PyPI.
pip - The standard package installer for Python, fetching from PyPI.
Virtual Environment - An isolated Python install with its own packages and versions.
Jupyter Notebook - Web-based interactive document mixing runnable Python cells, output, and Markdown.
NumPy - The foundational Python library for fast numerical arrays and vectorized math.
ndarray - NumPy's N-dimensional array - homogeneous, fixed-size, contiguous memory.
pandas - The standard Python library for tabular and time-series data analysis.
DataFrame - pandas' 2D labeled table - rows have an index, columns have names and dtypes.
Matplotlib - The most widely used Python plotting library - substrate for most other plot libs.
scikit-learn - Standard Python library for classical ML, built on a unified estimator API.