Data Science Cheatsheet PDF
Explore essential data science concepts with this cheatsheet PDF. Understand data cleaning, exploratory analysis, probability, feature engineering, and fundamental machine learning principles to build a solid foundation for practical data science tasks.
Data science involves a wide range of concepts, from statistics and data preprocessing to feature engineering and machine learning. It’s easy to forget formulas, workflows, or key principles under time pressure. This lesson will help us understand and connect these core ideas, enabling us to apply them confidently in projects, interviews, or analysis.
Data understanding and preparation
Before analyzing data, it’s essential to clean, preprocess, and structure it. High-quality, well-prepared data forms the backbone of accurate insights and effective models. Understanding the nature of the data allows us to detect patterns, prevent errors, and make informed decisions.
The following are the core techniques:
Handling missing values: Strategies include deletion (removing rows or columns), mean/median/mode imputation, or predictive imputation using ML models.
Outlier detection and treatment: Identify extreme values and decide whether to remove, cap, or transform them.
Data transformation: Scale numerical features, encode categorical variables, bin continuous data, or apply log/power transformations to prepare data. ...