Basic Statistical Concepts
Introduction to the fundamental pillars of statistics in ML: Populations vs. Samples, Descriptive vs. Inferential statistics, and Data Types.
Introduction to the fundamental pillars of statistics in ML: Populations vs. Samples, Descriptive vs. Inferential statistics, and Data Types.
Understanding scalars, the fundamental single-number quantities in linear algebra and machine learning.
Understanding Python's dynamic typing system, memory management, and the core data types essential for data science.