6 docs tagged with "pandas"

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.

Techniques for identifying, analyzing, and resolving missing values in datasets using deletion and imputation strategies.

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.

A comprehensive guide to creating, transforming, and selecting features to maximize Machine Learning model performance.