50 Data Science Acronyms and Their Full Forms

Useful Data Science Acronyms

In the era of minimalism, the IT field is also affected widely by the minimalist culture. Social media trends have started a new culture of using acronyms all around the internet. Acronyms are not new; they have been used in computer science since the beginning.

In this article, we will share the 50 most used data science acronyms that all data professionals must know.

50 Most Used Data Science Acronyms

1. ANOVA : Analysis of Variance
2. AUC : Area Under the Curve
3. BART: Bidirectional and Auto-Regressive Transformer
4. BDA: Big Data Analytics
5. BERT: Bidirectional Encoder Representations from Transformers
6. CFDS: Customer-Facing Data Scientist
7. CV: Cross Validation
8. CNN : Convolutional Neural Network
9. DL: Deep Learning
10. DNN: Deep Neural Network or Deconvolutional Neural Network
11. DQ: Data Quality
12. EDA: Exploratory Data Analysis
13. ELMO: Embeddings from Language Models
14. GBM: Gradient Boosting Machine
15. GLM: Generalized Linear Model
16. GRU: Gated Recurrent Unit
17. HMM : Hidden Marcov Model
18. ICA: Independent Component Analysis
19. JSON: JavaScript Object Notation
20. kNN: k-Nearest Neighbors
21. LB: LeaderBoard
22. LDA: Latent Dirichlet Allocation or Linear Discriminant Analysis
23. LLE : Locally Linear Embedding
24. LOOCV : Leave-One-Out cross-validation
25. LpO CV : Leave-p-out cross-validation
26. LSA/LSI: Latent Semantic Allocation/Indexing
27. LSTM: Long Short Term Memory
28. MAPE: Mean Absolute Percentage Error
29. MARGE: Multilingual Autoencoder that Retrieves and Generates
30. MCMC : Markov Chain Monte Carlo
31. MDS : Multi-Dimensional Scaling
32. MSE: Mean Squared Error
33. NLDR: Non-Linear Dimensionality Reduction
34. NLP : Natural Language Processing
35. NMF: Non-Negative Matrix Factorization
36. OOF: Out Of Fold
37. PCA: Principal Component Analysis
38. pLSA: Probabilistic Latent Semantic Allocation
39. R2 : R-squared
40. RF: Random Forest
41. RFE: Recursive Feature Elimination
42. RMSLE : Root Mean Squared Logarithmic Error
43. RNN: Recurrent Neural Network
44. ROC : Receiver Operating Characteristic
45. SMOTE: Synthetic Minority Over-sampling Technique
46. SQL: Structured Query Language
47. SVM: Support Vector Machine
48. tf-idf: term frequency, inverse document frequency
49. t-SNE: t-Distributed Stochastic Neighbor Embedding
50. XML: Extensible Markup Language

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