CSV: The Universal Data Language
Understanding the Comma-Separated Values format: its role in ML, performance trade-offs, and best practices for ingestion.
Understanding the Comma-Separated Values format: its role in ML, performance trade-offs, and best practices for ingestion.
Handling .xlsx and .xls files in ML pipelines: managing multi-sheet workbooks, data types, and conversion pitfalls.
Mastering DataFrames, Series, and data cleaning techniques: the essential toolkit for exploratory data analysis (EDA).
Mastering the Python essentials required for ML: from data structures to vectorization and the scientific ecosystem.