THE DATA SCIENCE INTERVIEW BOOK
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  • About
  • Log
  • Mathematical Motivation
  • STATISTICS
    • Probability Basics
    • Probability Distribution
    • Central Limit Theorem
    • Bayesian vs Frequentist Reasoning
    • Hypothesis Testing
    • ⚠️A/B test
  • MODEL BUILDING
    • Overview
    • Data
      • Scaling
      • Missing Value
      • Outlier
      • ⚠️Sampling
      • Categorical Variable
    • Hyperparameter Optimization
  • Algorithms
    • Overview
    • Bias/Variance Tradeoff
    • Regression
    • Generative vs Discriminative Models
    • Classification
    • ⚠️Clustering
    • Tree based approaches
    • Time Series Analysis
    • Anomaly Detection
    • Big O
  • NEURAL NETWORK
    • Neural Network
    • ⚠️Recurrent Neural Network
  • NLP
    • Lexical Processing
    • Syntactic Processing
    • Transformers
  • BUSINESS INTELLIGENCE
    • ⚠️Power BI
      • Charts
      • Problems
    • Visualization
  • PYTHON
    • Theoretical
    • Basics
    • Data Manipulation
    • Statistics
    • NLP
    • Algorithms from scratch
      • Linear Regression
      • Logistic Regression
    • PySpark
  • ML OPS
    • Overview
    • GIT
    • Feature Store
  • SQL
    • Basics
    • Joins
    • Temporary Datasets
    • Windows Functions
    • Time
    • Functions & Stored Proc
    • Index
    • Performance Tuning
    • Problems
  • ⚠️EXCEL
    • Excel Basics
    • Data Manipulation
    • Time and Date
    • Python in Excel
  • MACHINE LEARNING FRAMEWORKS
    • PyCaret
    • ⚠️Tensorflow
  • ANALYTICAL THINKING
    • Business Scenarios
    • ⚠️Industry Application
    • Behavioral/Management
  • Generative AI
    • Vector Database
    • LLMs
  • CHEAT SHEETS
    • NumPy
    • Pandas
    • Pyspark
    • SQL
    • Statistics
    • RegEx
    • Git
    • Power BI
    • Python Basics
    • Keras
    • R Basics
  • POLICIES
    • PRIVACY NOTICE
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  1. CHEAT SHEETS

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