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Machine learning acronyms and abbreviations banner

Machine learning acronyms and abbreviations 🤖

A comprehensive list of ML and AI acronyms and abbreviations. Feel free to ⭐ it!

Machine learning is rapidly growing, creating more mysterious acronyms and abbreviations that might be challenging to follow, especially for beginners. This abbreviations list was created when I collected all acronyms from my Ph.D. thesis. Surprised by the enormous number, I searched through the web to copy and paste them to save time on writing. I found a few lists, but none covered all I needed. I decided to gather all this info in a single Table to make it easier to fellow ML enthusiasts.

Sources 📖

Contributing 📝

Feel free to:

  • add any ML-related abbreviation,
  • add the definition alone,
  • add an issue.

Currently, ~30% of abbreviations have descriptions, so feel free to add them! It should be a brief and concise one-liner rather than explain the whole subject. The purpose is to quickly find the meaning of an abbreviation, and the given definition helps to understand if it matches the context. Abbreviations should be in alphabetical order.

I have added a link to the online doc with all abbreviations to make it easier for you to contribute. Feel free to add a new one and sort the table automatically. You can copy the table from Google Sheets to the markdown table generator: https://www.tablesgenerator.com/markdown_tables.

The list 📑

Acronym Description Definition
ACC ACCuracy Accuracy is a metric for evaluating classification models.
ACE Alternating conditional expectation (ACE) algorithm An algorithm to find the optimal transformations between the response variable and predictor variables in regression analysis.
ADA AdaBoosted Decision Trees Using AdaBoost to improve performance in decision trees.
AdaBoost Adaptive Boosting A statistical classification meta-algorithm that can be used in conjunction with many other types of learning algorithms to improve performance.
AdR AdaBoostRegressor Using AdaBoost to improve performance in regression.
ADT Automatic Drum Transcription Methods that aim to detect drum events in polyphonic music
AE AutoEncoder A type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning)
AGI Artificial General Intelligence The hypothetical ability of an intelligent agent to understand or learn any intellectual task that a human being can
AI Artificial Intelligence The simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.
AIWPSO Adaptive Inertia Weight Particle Swarm Optimization An optimization algorithm using an individual search ability (ISA) to indicate whether each particle lacks global exploration or local exploitation abilities in each dimension.
AM Activation Maximization A method to visualize neural networks and aims to maximize the activation of certain neurons.
AMT Automatic Music Transcription Computational algorithms that convert acoustic music signals into some form of music notation
ANN Artificial Neural Network A collection of connected computational units or nodes called neurons arranged in multiple computational layers.
AR Augmented Reality An interactive experience of a real-world environment where the objects that reside in the real world are enhanced by computer-generated perceptual information sometimes across multiple sensory modalities.
ARNN Anticipation Recurrent Neural Network
AUC Area Under the (ROC) Curve Probability of confidence in a model to accurately predict positive outcomes for actual positive instances
BDT Boosted Decision Tree
BERT Bidirectional Encoder Representation from Transformers Commonly used transformer-based language model.
BiFPN Bidirectional Feature Pyramid Network
BILSTM Bidirectional Long Short-Term Memory A bidirectional recurrent neural network architecture (see LSTM).
BLEU Bilingual Evaluation Understudy A score of the effectiveness of translating one language into another one.
BN Bayesian Network A probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG).
BNN Bayesian Neural Network A type of artificial neural network built by introducing random variations into the network either by giving the network's artificial neurons stochastic transfer functions either by giving the network's artificial neurons stochastic transfer functions or by giving them stochastic weights
BP BackPropagation A widely used algorithm for training feedforward neural networks.
BPMF Bayesian Probabilistic Matrix Factorization
BPTT Backpropagation Through Time A gradient-based technique for training certain types of recurrent neural networks (e.g. Elman networks).
BQML Big Query Machine Learning
BRNN Bidirectional Recurrent Neural Network
BRR Bayesian Ridge Regression
CAE Contractive AutoEncoder
CALA Continuous Action-set Learning Automata
CART Classification And Regression Tree
CAV Concept Activation Vectors Explainability method that provides an interpretation of a neural net's internal state in terms of human-friendly concepts.
CBI Counterfactual Bias Insertion
CBOW Continuous Bag of Words
CDBN Convolutional Deep Belief Networks A type of deep artificial neural network composed of multiple layers of convolutional restricted Boltzmann machines stacked together.
CE Cross-Entropy
CEC Constant Error Carousel
CF Common Features
CLNN ConditionaL Neural Networks
CMAC Cerebellar Model Articulation Controller
CMMs Conditional Markov Model A graphical model for sequence labeling that combines features of hidden Markov models (HMMs) and maximum entropy (MaxEnt) models. Also known as maximum-entropy Markov model (MEMM).
CNN Convolutional Neural Network A class of artificial neural network (ANN) most commonly applied to analyze visual imagery
ConvNet Convolutional Neural Network A class of artificial neural network (ANN) most commonly applied to analyze visual imagery
CRBM Conditional Restricted Boltzmann Machine
CRFs Conditional Random Fields
CRNN Convolutional Recurrent Neural Network
CTC Connectionist Temporal Classification
CTR Collaborative Topic Regression
CV Coefficient of Variation Intra-cluster similarity to measure the accuracy of unsupervised classification models based on clusters
CV Computer Vision
CV Cross Validation Resampling method for training, validation and testing a model across different iterations on portions of the full data set.
CSLR Continuous Sign Language Recognition Sign language recognition and understanding (continuous using not only single words but whole phrases) getting knowledge about the meaning of signs essential for SLT.
DAAF Data Augmentation and Auxiliary Feature
DAE Denoising AutoEncoder or Deep AutoEncoder
DBM Deep Boltzmann Machine
DBN Deep Belief Network
DBSCAN Density-Based Spatial Clustering of Applications with Noise
DCGAN Deep Convolutional Generative Adversarial Network
DCMDN Deep Convolutional Mixture Density Network
DE Differential Evolution
DeconvNet DeConvolutional Neural Network
DeepLIFT Deep Learning Important FeaTures
DL Deep Learning
DNN Deep Neural Network
DQN Deep Q-Network
DR Detection Rate Represents the sensitivity or detection rate of a model
DSN Deep Stacking Network
DT Decision Tree
DTD Deep Taylor Decomposition
DWT Discrete Wavelet Transform
ELECTRA Efficiently Learning an Encoder that Classifies Token Replacements Accurately
ELM Extreme Learning Machine
ELMo Embeddings from Language Models
ELU Exponential Linear Unit
EM Expectation maximization
EMD Entropy Minimization Discretization
ERNIE Enhanced Representation through kNowledge IntEgration
ETL Pipeline Extract Transform Load Pipeline
EXT Extremely Randomized Trees
F1 Score Harmonic Precision-Recall Mean
FALA Finite Action-set Learning Automata
FC Fully-Connected Layers where all the inputs from one layer are connected to every activation unit of the next layer.
FC-CNN Fully Convolutional Convolutional Neural Network A neural network that only performs convolution (and subsampling or upsampling) operations.
FC-LSTM Fully Connected Long Short-Term Memory A fully connected neural network to combine the spatial information of surrounding stations (see LSTM and FC).
FCM Fuzzy C-Means
FCN Fully Convolutional Network A neural network that only performs convolution (and subsampling or upsampling) operations.
FFT Fast Fourier transform
FLOP Floating Point Operations A unit of measure of the amount of mathematical computations often used to describe the complexity of a neural network.
FLOPS Floating Point Operations Per Second A unit of measure of computer performance
FNN Feedforward Neural Network
FNR False Negative Rate Proportion of actual positives predicted as negatives
FPN Feature Pyramid Network
FPR False Positive Rate Proportion of actual negatives predicted as positives
FST Finite state transducer
FWIoU Frequency Weighted Intersection over Union Metric in segmentation/object detection tasks. Weighted average of IoU's over classes, where weights depend on class frequency.
GA Genetic Algorithm
GALE Global Aggregations of Local Explanations Explainability method that aggregates local explanations (of single prediction) into an explanation how the whole model works.
GAM Generalized Additive Model
GAM Global Attribution Mapping
GAMLSS Generalized Additive Models for Location, Scale and Shape
GAN Generative Adversarial Network A deep-learning-based generative model using "indirect" training through the discriminator another neural network that is able to tell how much an input is "realistic" which itself is also being updated dynamically.
GAP Global Average Pooling
GBRCN Gradient-Boosting Random Convolutional Network
GD Gradient Descent An optimization algorithm used to minimize some function by iteratively moving in the direction of steepest descent as defined by the negative of the gradient
GEBI Global Explanation for Bias Identification Explainability method that aggregates local explanations (of single prediction) into a global explanation with the goal of finding biases and systematic errors in decision making.
GFNN Gradient Frequency Neural Networks
GLCM Gray Level Co-occurrence Matrix
Gloss2Text A task of transforming raw glosses into meaningful sentences.
GloVE Global Vectors
GMM Gaussian mixture model A probabilistic model that assumes all the data points are generated from a mixture of a finite number of Gaussian distributions with unknown parameters.
GPR Gaussian Process Regression
GPT Generative Pre-trained Transformer An autoregressive language model that uses deep learning to produce human-like text.
GradCAM GRADient-weighted Class Activation Mapping
HamNoSys Hamburg Sign Language Notation System An annotation system that describes sign language symbols
HAN Hierarchical Attention Network
HCA Hierarchical Clustering Analysis
HDP Hierarchical Dirichlet process
HHDS HipHop Dataset
hLDA Hierarchical Latent Dirichlet allocation
HMM Hidden Markov Model
HNN Hopfield Neural Network
i.i.d Independent and Identically Distributed
ID3 Iterative Dichotomiser 3
IDR Input dependence rate
IIR Input independence rate
INFD Explanation Infidelity
IoU Jaccard index (intersection over union) Metric in segmentation/object detection tasks. Ratio of areas of intersection and union of two (segmentation) boxes, corresponding to e.g. prediction and label.
ISIC International Skin Imaging Collaboration
k-NN k-Nearest Neighbor
KDE Kernel Density Estimation
KL Kullback Leibler (KL) divergence
kNN k-Nearest Neighbours A non-parametric supervised learning method used for classification and regression.
KRR Kernel Ridge Regression
LDA Latent Dirichlet Allocation A generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar.
LDA Linear Discriminant Analysis
LDADE Latent Dirichlet Allocation Differential Evolution
LightGBM Light Gradient-Boosting Machine Gradient boosting framework that uses tree based learning algorithms, originally developed by Microsoft
LIME Local Interpretable Model-agnostic Explanations
LRP Layer-wise Relevance Propagation
LSA Latent semantic analysis
LSI Latent Semantic Indexing
LSTM Long Short-Term Memory A recurrent neural network can process not only single data points (such as images) but also entire sequences of data (such as speech or video).
LTR Learning To Rank
LVQ Learning Vector Quantization
MADE Masked Autoencoder for Distribution Estimation
MAE Mean Absolute Error Average of the absolute error between the actual and predicted values
MAF Masked Autoregressive Flows
MAP Maximum A Posteriori (MAP) Estimation
MAPE Mean Absolute Prediction Error Percentage of the error between the actual and predicted values
MARS Multivariate Adaptive Regression Spline Non-parametric regression technique, extends linear models. Note that the name is trademarked, opem source implementations are often called "EARTH"
MART Multiple Additive Regression Tree
MaxEnt Maximum Entropy Entropy a scientific concept as well as a measurable physical property that is most commonly associated with a state of disorderrandomnessor uncertainty.
MCLNN Masked ConditionaL Neural Networks
MCMC Markov Chain Monte Carlo
MCS Model contrast score
MDL Minimum description length (MDL) principle
MDN Mixture Density Network
MDP Markov Decision Process
MDRNN Multidimensional recurrent neural network
MER Music Emotion Recognition
MINT Mutual Information based Transductive Feature Selection
MIoU Mean Intersection over Union Metric in segmentation/object detection tasks. Mean of IoU's over classes.
ML Machine Learning The study of computer algorithms that can improve automatically through experience and by the use of data.
MLE Maximum Likelihood Estimation
MLM Music Language Models
MLP Multi-Layer Perceptron A fully connected class of feedforward artificial neural network
MPA Mean Pixel Accuracy Metric in segmentation/object detection tasks. Average ratio of correctly classified pixels by class.
MRR Mean Reciprocal Rank
MRS Music Recommender System
MSDAE Modified Sparse Denoising Autoencoder
MSE Mean Squared Error Average of the squares of the error between the actual and predicted values
MSR Music Style Recognition
NAS Neural Architecture Search A technique for automating the design of artificial neural networks.
NB Na ̈ıve Bayes
NBKE Na ̈ıve Bayes with Kernel Estimation
NER Named Entity Recognition
NERQ Named Entity Recognition in Query
NF Normalizing Flow
NFL No Free Lunch (NFL) theorem
NLP Natural Language Processing
NLT Neural Machine Translation An approach to translation with the use of a neural network to predict a sequence of words.
NMS Non Maximum Suppression A technique used in Object Detection for removing redundand overlapping bounding boxes
NN Neural Network
NNMODFF Neural Network based Multi-Onset Detection Function Fusion
NPE Neural Physical Engine
NRMSE Normalized RMSE Cross-entropy Metric based on the logistic function that measures the error between the actual and predicted values.
NST Neural Style Transfer A method that uses of deep neural networks for transfering style.
NTM Neural Turing Machine
ODF Onset Detection Function
OLR Ordinary Linear Regression
OLS Ordinary Least Squares
PA Pixel Accuracy Metric in segmentation/object detection tasks. Ratio of correctly classified over total number of pixels.
PACO Poisson Additive Co-Clustering
PCA Principal Component Analysis The process of computing the principal components and using them to perform a change of basis on the data sometimes using only the first few principal components and ignoring the rest.
PEGASUS Pre-training with Extracted Gap-Sentences for Abstractive Summarization
PLSI Probabilistic Latent Semantic Indexing
PM Project Manager
PMF Probabilistic Matrix Factorization
PMI Pointwise Mutual Information
PNN Probabilistic Neural Network
POC Proof of Concept
POMDP Partially Observable Markov Decision Process
POS Part of Speech (POS) Tagging
PPMI Positive Pointwise Mutual Information
PReLU Parametric Rectified Linear Unit-Yor Topic Modeling
PU Positive Unlabaled Machine learning paradigma to learn from only positive and unlabeled data.
PYTM Pitman
RandNN Random Neural Network
RANSAC RANdom SAmple Consensus
RBF Radial Basis Function
RBFNN Radial Basis Function Neural Network
RBM Restricted Boltzmann Machine
ReLU Rectified Linear Unit An activation function that allow fast and effective training of deep neural architectures on large and complex datasets.
REPTree Reduced Error Pruning Tree
RF Random Forest
RGB Red Green Blue color model An additive color model used for display of images
RICNN Rotation Invariant Convolutional Neural Network
RIM Recurrent Interence Machines
RIPPER Repeated Incremental Pruning to Produce Error Reduction
RL Reinforcement Learning
RLFM Regression based latent factors
RMSE Root MSE Squared root of MSE
RNN Recurrent Neural Network
RNNLM Recurrent Neural Network Language Model (RNNLM)
RoBERTa Robustly Optimized BERT Pretraining Approach Commonly used transformer-based language model.
ROC Received Operating Characteristic Curve that plots TPR versus FPR at different parameter settings
ROI Region Of Interest
RR Ridge Regression
RTRL Real-Time Recurrent Learning
SAE Stacked AE
SARSA State-Action-Reward-State-Action
SBM Stochastic block model
SBO Structured Bayesian optimization
SBSE Search-based software engineering
SCH Stochastic convex hull
SDAE Stacked DAE
seq2seq Sequence to Sequence Learning Desribes training approach to convert sequences from one domain (e.g. sentences in English) to sequences in another domain (e.g. the same sentences translated to French).
SER Sentence Error Rate
SGBoost Stochastic Gradient Boosting
SGD Stochastic Gradient Descent
SGVB Stochastic Gradient Variational Bayes
SHAP SHapley Additive exPlanation
SHLLE Supervised Hessian Locally Linear Embedding
Sign2(Gloss+Text) Sign to Gloss and Text A two-step process requires joint learning of sign language recognition and translation.
Sign2Gloss A one to one translation from the single sign to the single gloss.
Sign2Text A task of full translation from the sign language into the spoken one grammar and syntax are included.
SLP Single-Layer Perceptron
SLRT Sign Language Recognition Transformer an encoder transformer model trained to predict sign gloss sequences it takes spatial embeddings and learns spatio-temporal representations.
SLT Sign Language Translation A full translation of signs to a spoken language.
SLTT Sign Language Translation Transformer an autoregressive transformer decoder model trained on output from SLRT to predict one word at a time to generate the corresponding spoken language sentence.
SMBO Sequential Model-Based Optimization
SOM Self-Organizing Map A self-organizing map (SOM) or self-organizing feature map (SOFM) is an unsupervised machine learning technique used to produce a low-dimensional (typically two-dimensional) representation of a higher dimensional data set while preserving the topological structure of the data
SpRay Spectral Relevance Analysis Global explainability method using spectral clustering and local explanations (LRP).
SSD Single-Shot Detector A type of object detector that consists of a single stage. Some examples are YOLO RetinaNet and EfficientDet.
SSL Self-Supervised Learning
SSVM Smooth support vector machine
ST Style Transfer An algorithm that allows to tranfer properties of one object to another (i.e. transfer painitning style to a photography).
STDA Style Transfer Data Augmentation A method using style transfer to augment dataset.
STL Selt-Taught Learning
SVD Singing Voice Detection
SVD Singular Value Decomposition
SVM Support Vector Machine Supervised learning models with associated learning algorithms that analyze data for classification and regression analysis.
SVR Support Vector Regression Supervised learning models with associated learning algorithms that analyze data for regression analysis.
SVS Singing Voice Separation
t-SNE t-distributed stochastic neighbor embedding
T5 Text-To-Text Transfer Transformer Transformer based language model that uses a text-to-text approach.
TD Temporal Difference
TDA Targeted Data Augmentation
TGAN Temporal Generative Adversarial Network
THAID THeta Automatic Interaction Detection
TINT Tree-Interpreter
TLFN Time-Lagged Feedforward Neural Network
TNR True Negative Rate Proportion of actual negatives that are correctly predicted
TPR True Positive Rate Proportion of actual positives that are correctly predicted
TRPO Trust Region Policy Optimization
ULMFiT Universal Language Model Fine-Tuning
V-Net Volumetric Convolutional neural network 3D image segmentation based on a volumetric fully convolutional neural network
VAD Voice Activity Detection
VAE Variational AutoEncoder An artificial neural network architecture belonging to the families of probabilistic graphical models and variational Bayesian methods.
VGG Visual Geometry Group Popular deep convolutional model designed for classification.
VPNN Vector Product Neural Network
VQ-VAE Vector Quantized Variational Autoencoders
VR Virtual Reality
WER Word Error Rate metric to measure performance used in NLP solutions e.g. in automatic speech recognition (ASR).
WFST Weighted finite-state transducer (WFST)
WMA Weighted Majority Algorithm
WPE Weighted Prediction Error
XAI Explainable Artificial Intelligence A set of processes and methods to make machine learning algorithms and its results more interpretable.
XGBoost eXtreme Gradient Boosting
YOLO You Only Look Once Fast object detection algorithm.

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