Terms

Artificial Intelligence Terms

See also: artificial intelligence terms

AI Agents

AI Monarchy

AI Project Management

Art

Artificial general intelligence (AGI)

AudioCraft

Backdooring LLMs

Bard

BERT

Burstiness

Completion - new text generated (output) by the LLM after you inference it with the prompt

Controversies

CodeGen

ControlNet

Copyright

CUDA

Cursor Rules

Custom GPTs

Dark Factory

Dead internet theory

Diffusion Models

DreamStudio

Emergent Abilities (Emergent Abilities of Large Language Models)

Ethics

Few shot

Foundation models

GPT

GPT-1

GPT-2

GPT-3

GPT-4

Grok 3 Jailbreak

hallucinations

HuggingGPT

image generator

LaMDA

LangChain - Prompt templates, Agents, Memory, Parametric knowledge, Source knowledge, Context window,

Large language models (LLMs)

Large language models ranking

LLM Anxiety

Manipulation problem

Manus AI

Minimum Viable Agent

Model hubs

Neural network

One shot

OpenAI

OpenAI Gym

OpenAI Gym Retro

OpenAI Universe

Perplexity

PoisonGPT

Pre-trained / Pretraining

Presentations

Prompt

Prompt engineering

Prompt engineering for image generation

Prompt engineering for text generation

Prompt extraction

Prompt injection

Purple Llama

PyTorch

Q* OpenAI

Segment Anything - cut out any object in an image, by Meta

SEO for ChatGPT

Stability AI

Text-to-3D

Text-to-audio

Text-to-image

Text-to-video

The Pile

Tokens

Transformers

Unstable Diffusion

Vector database

Vector embeddings

Vibe coding

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Machine Learning Terms

See also: Machine learning terms

Fundamentals
Natural Language Processing - Language Evaluation
Fairness
Decision Forests
Reinforcement Learning
Computer Vision - Image Models
Sequence Models
Clustering
Recommendation Systems
TensorFlow
Google Cloud

All ML Terms

See also: Machine learning terms/All

• A/B testing
• accuracy
• action
• activation function
• active learning
• AdaGrad
• agent
• agglomerative clustering
• anomaly detection
• AR
• area under the PR curve
• area under the ROC curve
• artificial general intelligence
• artificial intelligence
• attention
• attribute
• attribute sampling
• AUC (Area under the ROC curve)
• augmented reality
• automation bias
• average precision
• axis-aligned condition
• backpropagation
• bagging
• bag of words
• baseline
• batch
• batch normalization
• batch size
• Bayesian neural network
• Bayesian optimization
• Bellman equation
• BERT (Bidirectional Encoder Representations from Transformers)
• bias (ethics/fairness)
• bias (math) or bias term
• bigram
• bidirectional
• bidirectional language model
• binary classification
• binary condition
• binning
• BLEU (Bilingual Evaluation Understudy)
• boosting
• bounding box
• broadcasting
• bucketing
• calibration layer
• candidate generation
• candidate sampling
• categorical data
• causal language model
• centroid
• centroid-based clustering
• checkpoint
• class
• classification model
• classification threshold
• class-imbalanced dataset
• clipping
• Cloud TPU
• clustering
• co-adaptation
• collaborative filtering
• condition
• confirmation bias
• confusion matrix
• continuous feature
• convenience sampling
• convergence
• convex function
• convex optimization
• convex set
• convolution
• convolutional filter
• convolutional layer
• convolutional neural network
• convolutional operation
• cost
• co-training
• counterfactual fairness
• coverage bias
• crash blossom
• critic
• cross-entropy
• cross-validation
• data analysis
• data augmentation
• DataFrame
• data parallelism
• data set or dataset
• Dataset API (tf.data)
• decision boundary
• decision forest
• decision threshold
• decision tree
• deep model
• decoder
• deep neural network
• Deep Q-Network (DQN)
• demographic parity
• denoising
• dense feature
• dense layer
• depth
• depthwise separable convolutional neural network (sepCNN)
• derived label
• device
• dimension reduction
• dimensions
• discrete feature
• discriminative model
• discriminator
• disparate impact
• disparate treatment
• divisive clustering
• downsampling
• DQN
• dropout regularization
• dynamic
• dynamic model
• eager execution
• early stopping
• earth mover's distance (EMD)
• embedding layer
• embedding space
• embedding vector
• empirical risk minimization (ERM)
• encoder
• ensemble
• entropy
• environment
• episode
• epoch
• epsilon greedy policy
• equality of opportunity
• equalized odds
• Estimator
• example
• experience replay
• experimenter's bias
• exploding gradient problem
• fairness constraint
• fairness metric
• false negative (FN)
• false negative rate
• false positive (FP)
• false positive rate (FPR)
• feature
• feature cross
• feature engineering
• feature extraction
• feature importances
• feature set
• feature spec
• feature vector
• federated learning
• feedback loop
• feedforward neural network (FFN)
• few-shot learning
• fine tuning
• forget gate
• full softmax
• fully connected layer
• GAN
• generalization
• generalization curve
• generalized linear model
• generative adversarial network (GAN)
• generative model
• generator
• GPT (Generative Pre-trained Transformer)
• gini impurity
• gradient
• gradient boosting
• gradient boosted (decision) trees (GBT)
• gradient clipping
• gradient descent
• graph
• graph execution
• greedy policy
• ground truth
• group attribution bias
• hallucination
• hashing
• heuristic
• hidden layer
• hierarchical clustering
• hinge loss
• holdout data
• hyperparameter
• hyperplane
• i.i.d.
• image recognition
• imbalanced dataset
• implicit bias
• incompatibility of fairness metrics
• independently and identically distributed (i.i.d)
• individual fairness
• inference
• inference path
• information gain
• in-group bias
• input layer
• in-set condition
• instance
• interpretability
• inter-rater agreement
• intersection over union (IoU)
• IoU
• item matrix
• items
• iteration
• Keras
• keypoints
• Kernel Support Vector Machines (KSVMs)
• k-means
• k-median
• L0 regularization
• L1 loss
• L1 regularization
• L2 loss
• L2 regularization
• label
• labeled example
• LaMDA (Language Model for Dialogue Applications)
• lambda
• landmarks
• language model
• large language model
• layer
• Layers API (tf.layers)
• leaf
• learning rate
• least squares regression
• linear model
• linear
• linear regression
• logistic regression
• logits
• Log Loss
• log-odds
• Long Short-Term Memory (LSTM)
• loss
• loss curve
• loss function
• loss surface
• LSTM
• machine learning
• majority class
• Markov decision process (MDP)
• Markov property
• masked language model
• matplotlib
• matrix factorization
• Mean Absolute Error (MAE)
• Mean Squared Error (MSE)
• metric
• meta-learning
• Metrics API (tf.metrics)
• mini-batch
• mini-batch stochastic gradient descent
• minimax loss
• minority class
• ML
• MNIST
• modality
• model
• model capacity
• model parallelism
• model training
• Momentum
• multi-class classification
• multi-class logistic regression
• multi-head self-attention
• multimodal model
• multinomial classification
• multinomial regression
• NaN trap
• natural language understanding
• negative class
• neural network
• neuron
• N-gram
• NLU
• node (neural network)
• node (TensorFlow graph)
• node (decision tree)
• noise
• non-binary condition
• nonlinear
• non-response bias
• nonstationarity
• normalization
• novelty detection
• numerical data
• NumPy
• objective
• objective function
• oblique condition
• offline
• offline inference
• one-hot encoding
• one-shot learning
• one-vs.-all
• online
• online inference
• operation (op)
• out-of-bag evaluation (OOB evaluation)
• optimizer
• out-group homogeneity bias
• outlier detection
• outliers
• output layer
• overfitting
• oversampling
• pandas
• parameter
• Parameter Server (PS)
• parameter update
• partial derivative
• participation bias
• partitioning strategy
• perceptron
• performance
• permutation variable importances
• perplexity
• pipeline
• pipelining
• policy
• pooling
• positive class
• post-processing
• PR AUC (area under the PR curve)
• precision
• precision-recall curve
• prediction
• prediction bias
• predictive parity
• predictive rate parity
• preprocessing
• pre-trained model
• prior belief
• probabilistic regression model
• proxy (sensitive attributes)
• proxy labels
• Q-function
• Q-learning
• quantile
• quantile bucketing
• quantization
• queue
• random forest
• random policy
• ranking
• rank (ordinality)
• rank (Tensor)
• rater
• recall
• recommendation system
• Rectified Linear Unit (ReLU)
• recurrent neural network
• regression model
• regularization
• regularization rate
• reinforcement learning (RL)
• ReLU
• replay buffer
• reporting bias
• representation
• re-ranking
• return
• reward
• ridge regularization
• RNN
• ROC (receiver operating characteristic) Curve
• root
• root directory
• Root Mean Squared Error (RMSE)
• rotational invariance
• sampling bias
• sampling with replacement
• SavedModel
• Saver
• scalar
• scaling
• scikit-learn
• scoring
• selection bias
• self-attention (also called self-attention layer)
• self-supervised learning
• self-training
• semi-supervised learning
• sensitive attribute
• sentiment analysis
• sequence model
• sequence-to-sequence task
• serving
• shape (Tensor)
• shrinkage
• sigmoid function
• similarity measure
• size invariance
• sketching
• softmax
• sparse feature
• sparse representation
• sparse vector
• sparsity
• spatial pooling
• split
• splitter
• squared hinge loss
• squared loss
• stability
• staged training
• state
• state-action value function
• static
• static inference
• stationarity
• step
• step size
• stochastic gradient descent (SGD)
• stride
• structural risk minimization (SRM)
• subsampling
• summary
• supervised machine learning
• synthetic feature
• tabular Q-learning
• target
• target network
• temporal data
• Tensor
• TensorBoard
• TensorFlow
• TensorFlow Playground
• TensorFlow Serving
• Tensor Processing Unit (TPU)
• Tensor rank
• Tensor shape
• Tensor size
• termination condition
• test
• test loss
• test set
• tf.Example
• tf.keras
• threshold (for decision trees)
• time series analysis
• timestep
• token
• tower
• TPU
• TPU chip
• TPU device
• TPU master
• TPU node
• TPU Pod
• TPU resource
• TPU slice
• TPU type
• TPU worker
• training
• training loss
• training-serving skew
• training set
• trajectory
• transfer learning
• Transformer
• translational invariance
• trigram
• true negative (TN)
• true positive (TP)
• true positive rate (TPR)
• unawareness (to a sensitive attribute)
• underfitting
• undersampling
• unidirectional
• unidirectional language model
• unlabeled example
• unsupervised machine learning
• uplift modeling
• upweighting
• user matrix
• validation
• validation loss
• validation set
• vanishing gradient problem
• variable importances
• Wasserstein loss
• weight
• Weighted Alternating Least Squares (WALS)
• weighted sum
• wide model
• width
• wisdom of the crowd
• word embedding
• Z-score normalization