Our glossary page provides clear, concise definitions of key terms and concepts in the fields of Artificial Intelligence (AI), Machine Learning (ML), and Large Language Models (LLMs).
Glossary
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a
- Abductive Logic Programming
- Abstract Data Type
- ACID Transactions
- Activation Functions
- Active Learning in Machine Learning
- Adaptive Gradient Algorithm (AdaGrad)
- Adversarial Machine Learning
- Agent Evaluation
- Agent Observability
- Agent Planning
- Agent2Agent Protocol
- Agentic Chunking
- Agentic Memory
- Agentic Orchestration
- Agentic RAG
- Agentic Workflow
- AI Agent
- AI Agent Evaluation
- AI Agent Framework
- AI Agent Observability
- AI Center of Excellence (AI CoE)
- AI Content Moderation
- AI Copilots
- AI Data Labeling
- AI Fairness
- AI Firewall
- AI Model Validation
- AI Observability
- AI Risk Assessment
- AI Steerability
- AlpacaEval
- ANFIS
- Anomaly Detection
- Artificial Neural Network
- Attention in Machine Learning
- Attribute
- Auto-Encoder
- Automated Machine Learning
- AutoML
- Autonomous Agents
- Autoregressive Model
- Average Precision
- AWS Bedrock
- AWS Sagemaker
c
- Calibration Curve
- Canonical Schema
- Catastrophic Forgetting
- CatBoost
- Categorical Variables
- Causal Language Modeling (CLM)
- Chain-of-Thought
- Chain-of-Thought Prompting
- Chatbot Hallucinations
- ChatGLM
- CI/CD for Machine Learning
- Class Imbalance
- Classification Threshold
- Clustering Algorithms
- Clustering in Machine Learning
- Code Interpreter
- Complex Event Processing
- Computer Vision
- Confusion Matrix in Machine Learning
- Context Window
- Continuous Integration Model
- Continuous Validation
- Contrastive Learning
- Conversational Agent
- Convex Optimization
- Convolutional Neural Network
- Corrective RAG
- Cross-Lingual Language Models
- Cross-Validation Modeling
d
- Data Augmentation
- Data Binning
- Data Cleaning
- Data Decomposition
- Data Flywheel
- Data Granularity
- Data Logging
- Data Mart
- Data Science Platform
- Data Science Techniques
- Data Science Tools
- Data Vault
- Data Versioning
- Data Visualizations
- Data-Centric AI
- Datasets and Machine Learning
- Decision Boundary
- Decision Intelligence
- Decision Tree in Machine Learning
- Deep Belief Networks
- Deep Learning
- Deep Learning Algorithms
- Deep Q-Network
- Deep Reinforcement Learning
- Deep SHAP
- DeepEval
- Degradation Model
- DenseNet
- Density-Based Clustering
- Diffusion Models
- Dimensionality Reduction
- Direct Preference Optimization
- Dplyr
- Drift monitoring
l
- LangChain
- Large Action Models
- Learning Rate in Machine Learning
- Learning-to-Rank
- LightGBM
- Linear Regression
- LLama
- LLM Agents
- LLM Alignment
- LLM APIs
- LLM App Platforms
- LLM Benchmarks
- LLM Chatbot Evaluation
- LLM Cost
- LLM Debugger
- LLM Deployment
- LLM Distillation
- LLM Embeddings
- LLM Evaluation
- LLM Evaluation Framework
- LLM Fine Tuning
- LLM Gateway
- LLM Grounding
- LLM Guardrails
- LLM Inference
- LLM Interpretability
- LLM Jacking
- LLM Jailbreaking
- LLM Knowledge Base
- LLM Knowledge Graph
- LLM Leaderboards
- LLM Observability
- LLM Ontology
- LLM Orchestration
- LLM Output Consistency
- LLM Output Parsing
- LLM Overreliance
- LLM Parameters
- LLM Playground
- LLM Product Development
- LLM Quantization
- LLM Red Teaming
- LLM Regression Testing
- LLM Risk Assessment
- LLM Sleeper Agents
- LLM Stack Layers
- LLM Summarization
- LLM Summarization
- LLM Testing
- LLM Toxicity
- LLM Tracing
- LLM-as-a-Service
- LLMOps
- LLMs Hallucinations
- Local Interpretable Model-Agnostic Explanations (LIME)
- Logistic Regression
- Long Short-Term Memory (LSTM)
- Low-Rank Adaptation of Large Language Models
m
- Machine Learning
- Machine Learning Algorithm
- Machine Learning as a Service (MLaaS)
- Machine Learning Bias
- Machine Learning Checkpointing
- Machine Learning in Software Testing
- Machine Learning Inference
- Machine Learning Lifecycle
- Machine Learning Model Accuracy
- Machine Learning Model Deployment
- Machine Learning Model Evaluation
- Machine Learning Pipeline
- Machine Learning Workflows
- Masked Language Models (MLM)
- Mean Absolute Error
- Mean Absolute Percentage Error
- Mean Square Error (MSE)
- Memory-Augmented Neural Networks
- Meta-Learning
- METEOR Score
- Micro-Models
- Missing Values in Time Series
- Mixture of Experts
- ML Architecture
- ML Diagnostics
- ML Infrastructure
- ML Interpretability
- ML Model Card
- ML Model Management
- ML Model Validation
- ML Orchestration
- ML Performance Tracing
- ML Scalability
- ML Stack
- MLOps
- MLOps for Generative AI
- MLOps Framework
- MLOps Monitoring
- MMLU benchmark
- Model Behavior
- Model Calibration
- Model Collapse
- Model Distillation
- Model Drift
- Model Explainability
- Model Fairness
- Model Merging
- Model Monitoring
- Model Observability
- Model Parameters
- Model Registry
- Model Retraining
- Model Robustness
- Model Selection
- Model Tuning
- Model-Based Machine Learning
- Model-Driven Architecture
- Modular RAG
- MT-Bench
- MTEB
- Multi-Agent Tracing
- Multi-class Classification
- Multilayer Perceptron
- Multilingual LLM
p
- Pandas and Numpy
- Panoptic Segmentation
- Parameter-Efficient Fine-Tuning
- Parameter-Efficient Fine-Tuning (Prefix-Tuning)
- Pascal
- Pattern Matching
- Pattern Recognition
- PCA – Principal Component Analysis
- Permutation Importance
- Pooling Layers in CNN
- Population Stability Index
- Positional Encoding
- PR AUC
- Pre-trained Transformer
- Precision in Machine Learning
- Predictive Model Validation
- Preprocessing
- Probabilistic Classification
- Prompt Chaining
- Prompt Engineering
- Prompt Injection
- Prompt Injection Testing
- Prompt Management
- Prompt Optimization
- Prompt Playground
- Prompt Versioning
- Prototype Model
- PyTorch
r
- RAG Architecture
- RAG as a Service
- RAG Evaluation
- RAG Faithfulness
- RAG Hallucinations
- RAGAS
- Random Forests
- Random Initialization
- Reasoning Engine
- Recall in Machine Learning
- Recall-Oriented Understudy for Gisting Evaluation (ROUGE)
- Rectified Linear Unit (ReLU)
- Recurrent Neural Network
- Reference Distribution
- Regression
- Regression Algorithms
- Regularization Algorithms
- Regularization in Machine Learning
- Reinforcement Learning
- Reinforcement Learning from AI Feedback
- Reproducible AI
- ResNet
- Responsible AI
- Retrieval Augmented Generation
- Retrieval Augmented Generation (RAG) & Hallucinations
- Retrieval-augmented Generation
- Ridge Regression
- RLAIF
- RMSProp
- Robotic Process Automation (RPA)
- ROC (Receiver Operating Characteristic) Curve
- Root Mean Square Error (RMSE)
- Root-Cause Analysis
- Rotating Proxies
s
- Scikit-Learn
- Segment Anything Model
- Segmentation in Machine Learning
- Selective Sampling
- Semantic Router
- Semi-supervised Learning
- Sensitivity and Specificity of Machine Learning
- Sentiment Analysis
- seq2seq Model
- Shadow Deployment
- Shapley Values
- Six-Month Moratorium
- Sliding Window Attention
- Softmax Function
- Supervised Learning
- Support vector machine
- Support Vector Machines
- Surrogate Model
- Sycophancy in LLM
- Synthetic Data
- Synthetic Data Generation
t
- t-SNE
- Tabular Data
- TensorFlow
- Test Set in Machine Learning
- Text Generation Inference
- Time to First Token
- Top-1 Error Rate
- Training-Serving Skew
- Transfer Learning
- Transformer Neural Network
- Transformers Models
- Tree of Thoughts
- Tree-Based Models
- TreeSHAP
- Triplet Loss
- True Positive Rate
- Trulens
- Type 1 Error
- Type 2 Error
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