Coming across acronyms when learning an entirely new subject can be a bit confusing. They also make things appear more complicated than they are.
Here are 40 acronyms that you will need to learn as you gravitate toward Data Analysis.
| SN | ACRONYMS | MEANING |
| 1 | A/B testing | Comparison of two versions of a product or feature |
| 2 | AI | Artificial Intelligence |
| 3 | ANN | Artificial Neural Network |
| 4 | Bagging | Bootstrap Aggregating, |
| 5 | BI | Business Intelligence |
| 6 | CA | Cohort Analysis |
| 7 | CART | Classification and Regression Tree |
| 8 | CatBoost | Categorical Boosting |
| 9 | CLT | Central Limit Theorem |
| 10 | CNN | Convolutional Neural Network |
| 11 | DT | Decision Tree |
| 12 | DWH | Data Warehouse |
| 13 | EDA | Exploratory Data Analysis |
| 14 | ETL | Extract, Transform, Load |
| 15 | GBDT | Gradient Boosting Decision Tree |
| 16 | GBM | Gradient Boosting Machine |
| 17 | KNN | k Nearest Neighbors |
| 18 | KPI | Key Performance Indicator |
| 19 | LDA | Latent Dirichlet Allocation |
| 20 | LSTM | Long Short-Term Memory Network |
| 21 | MAP | Maximum a Posteriori Estimation |
| 22 | MBA | Market Basket Analysis |
| 23 | MCMC | Markov Chain Monte Carlo |
| 24 | ML | Machine Learning |
| 25 | MLE | Maximum Likelihood Estimation |
| 26 | MSE | Mean Squared Error |
| 27 | NLP | Natural Language Processing |
| 28 | NMF | Non-Negative Matrix Factorization |
| 29 | OLAP | Online Analytical Processing |
| 30 | PCA | Principal Component Analysis |
| 31 | PCY | Principal Coordinate Analysis |
| 32 | RCA | Root Cause Analysis |
| 33 | RDBMS | Relational Database Management System |
| 34 | RF | Random Forest |
| 35 | SAS | Statistical Analysis System |
| 36 | SPSS | Statistical Package for the Social Sciences |
| 37 | SQL | Structured Query Language |
| 38 | SVM | Support Vector Machine |
| 39 | VIF | Variance Inflation Factor |
| 40 | XRT | Extreme Gradient Boosting |
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