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Machine Learning model deployment

Machine Learning model deployment

$9.99

$109.99

"Machine Learning Model Deployment" is a focused course that equips you with the skills to deploy and manage machine learning models in production environments. You’ll learn to prepare models for deployment, explore various strategies including cloud-based solutions and containerization with Docker, and integrate models with applications. The course also covers performance monitoring, versioning, and scalability, providing you with practical experience and the knowledge needed to effectively manage machine learning models in real-world scenarios.

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Has discount
Expiry period Lifetime
Made in English
Last updated at Mon Jul 2024
Level
Beginner
Total lectures 19
Total quizzes 0
Total duration 14:11:55 Hours
Total enrolment 121
Number of reviews 24
Avg rating
Short description "Machine Learning Model Deployment" is a focused course that equips you with the skills to deploy and manage machine learning models in production environments. You’ll learn to prepare models for deployment, explore various strategies including cloud-based solutions and containerization with Docker, and integrate models with applications. The course also covers performance monitoring, versioning, and scalability, providing you with practical experience and the knowledge needed to effectively manage machine learning models in real-world scenarios.
Outcomes
  • Deployment Expertise: Ability to understand and execute the end-to-end process of deploying machine learning models into production.
  • Model Preparation Skills: Competence in preparing and packaging machine learning models for effective deployment.
  • Deployment Strategy Knowledge: Knowledge of various deployment strategies, including cloud-based solutions and containerization.
  • Application Integration: Skills in integrating machine learning models with applications and services for seamless functionality.
  • Performance Monitoring: Expertise in monitoring and maintaining deployed models, including handling performance issues and scalability.
Requirements

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