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#MLOpsLive Webinar: From Models to Meaning: Demonstrating AI Value in Production with Open Source Tooling - 9am PST, Feb 24

MLOps Glossary

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Model Tuning LLM Optimization Enterprise Data Science AI Infrastructure

All Terms

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a

Agentic Orchestration

AI Infrastructure

AI Proof of Concept

AI Tokenization

Arithmetic Intensity

Auto-Regressive Models

Automated Machine Learning

b

Baseline Models

c

Chain-of-Thought Prompting

CI/CD for Machine Learning

Classification Threshold

Continuous Validation

Cross-Validation

d

Data Pipeline Automation

Deep Learning Pipelines

Diffusion Models

Drift Monitoring

e

Embodied Agents

Enterprise Data Science

Excessive Agency

f

False Positive Rate

Feature Engineering

Fine-Tuning LLMs

Foundation Models

g

Generative Agents

GPU for Machine Learning

h

Holdout Dataset

Human in the Loop

Hyperpersonalization in AI

i

Image Processing Framework

k

Knowledge Distillation

Kubeflow Pipelines

Kubernetes for MLOps

l

Large Language Models

LLM as-a-Service

LLM Code Interpreter

LLM Code Interpreter

LLM Customization

LLM Hallucinations

LLM Interpretability

LLM Jailbreaking

LLM Optimization

LLM Orchestration

LLM Temperature

m

Machine Learning Infrastructure

Machine Learning Lifecycle

Mixture of Experts

ML Pipeline Tools

MLOps Governance

Model Accuracy in Machine Learning

Model Deployment

Model Evaluation

Model Management

Model Monitoring

Model Retraining

Model Serving Pipeline

n

o

On-Premise AI Platform

Open Source Model

Operationalizing ML

p

Prompt Engineering

Prompt Injection

Prompt Management

r

ReAct Prompting

Reasoning Engine

Risk Management

s

Self Reflection in LLMs

t

Transfer Learning

True Positive Rate

u

Unsupervised Machine Learning

v