THE DATA SCIENCE INTERVIEW BOOK
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Mathematical Motivation
STATISTICS
Probability Basics
Probability Distribution
Central Limit Theorem
Bayesian vs Frequentist Reasoning
Hypothesis Testing
⚠
A/B test
MODEL BUILDING
Overview
Data
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
Visualization
PYTHON
Theoretical
Basics
Data Manipulation
Statistics
NLP
Algorithms from scratch
ML OPS
GIT
SQL
Basics
Joins
Temporary Datasets
Windows Functions
Time
Functions
Problems
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EXCEL
Excel Basics
Data Manipulation
Time and Date
Python in Excel
MACHINE LEARNING FRAMEWORKS
PyCaret
⚠
Tensorflow
ANALYTICAL THINKING
Business Scenarios
⚠
Industry Application
Behavioral/Management
CHEAT SHEETS
NumPy
Pandas
SQL
Statistics
RegEx
Git
Power BI
Python Basics
Keras
R Basics
Generative AI
Vector Database
LLMs
POLICIES
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