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graviraja/MLOps-Basics

MLOps-Basics

> There is nothing magic about magic. The magician merely understands something simple which doesn’t appear to be simple or natural to the untrained a

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Builder

graviraja

graviraja

graviraja • individual

Stars

8,868

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Forks

1,768

Using upstream fork count

Open Issues

0

Activity Score

0/100

0 commits in 30d

Created

May 2, 2021

Project creation date

README Summary

> There is nothing magic about magic. The magician merely understands something simple which doesn’t appear to be simple or natural to the untrained audience. Once you learn how to hold a card while making your hand look empty, you only need practice before you, too, can “do magic.” – Jeffrey Friedl in the book Mastering Regular Expressions

Community Evaluation

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AI Dev Skills

Unmapped

Continuous Integration for MLExperiment TrackingML Model MonitoringMLOps EngineeringML Pipeline DevelopmentML Workflow ManagementModel DeploymentModel VersioningProduction ML Systems

Tags

Continuous Integration for MLExperiment TrackingML Model MonitoringMLOps EngineeringML Pipeline DevelopmentML Workflow ManagementModel DeploymentModel VersioningProduction ML SystemsAWSDVCDockerForkedHuggingFaceMLOpsMachine LearningMobileModel OptimizationMonitoringONNXPyTorchPython Web FrameworkScikit-learnTensorFlowTransformersTutorialWeights & Biases

Taxonomy

AI Trends

MLOpsProduction ML SystemsML Engineering

category

MLOps & InfrastructureFoundation ModelsModel TrainingObservability & MonitoringInference & ServingDev Tools & AutomationCloud & PlatformsLearning Resources

Deployment Context

CloudSelf-hosted

Skill Areas

MLOps EngineeringML Pipeline DevelopmentModel DeploymentML Workflow ManagementProduction ML SystemsML Model MonitoringContinuous Integration for MLModel VersioningExperiment Tracking

tag

AWSDVCDockerForkedHuggingFaceMLOpsMachine LearningMobileModel OptimizationMonitoringONNXPyTorchPython Web FrameworkScikit-learnTensorFlowTransformersTutorialWeights & Biases

Use Cases

ML Engineering EducationMLOps Workflow LearningProduction ML Pipeline ImplementationML Model Lifecycle Management

Recent Activity

Updated 1 years ago

7 Days

0

30 Days

0

90 Days

0

Quality

research
Quality
medium
Maturity
research

Categories

MLOps & InfrastructurePrimaryObservability & MonitoringInference & ServingDev Tools & AutomationCloud & PlatformsLearning ResourcesFoundation ModelsModel TrainingML Platform & InfrastructureSafety & AlignmentData Science & AnalyticsEdge & Mobile AIOther AI / ML

PM Skills

Scale & Reliability

Languages

Jupyter Notebook100.0%

Timeline

Project created
May 2, 2021
Forked
Nov 8, 2025
Your last push
1 years ago
Upstream last push
1 years ago
Tracked since
Sep 22, 2024

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