MLOps Glossary

Model Behavior

Data Ingestion

AI Tokenization

Transfer Learning

ML Stack

LLMOps

Large Language Models

Foundation Models

Risk Management

Data Pipeline Automation

Overfitting

Holdout Dataset

False Positive Rate

True Positive Rate

Recall

Classification Threshold

Baseline Models

Regression

Model Training

MLOps Governance

Automated Machine Learning

Cross-Validation

Continuous Validation

Model Tuning

Open Source Model

Noise in ML

Model Accuracy in Machine Learning

Explainable AI

Model Evaluation

Drift Monitoring

Model Serving Pipeline

Image Processing Framework

Kubernetes for MLOps

GPU for Machine Learning

Machine Learning Infrastructure

Model Retraining

Model Deployment

Deep Learning Pipelines

Model Management

Feature Vector

Model Serving

CI/CD for Machine Learning

Feature Engineering

Real Time ML

Unsupervised Machine Learning

Kubeflow Pipelines

Machine Learning Lifecycle

Model Monitoring

Concept Drift

Feature Store

ML Pipeline Tools

ML Pipeline

Operationalizing ML

Enterprise Data Science