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本番環境向けのMachine Learningモデル開発
中級スキルレベル
更新 2024/11無料でコースを始める
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TheoryMachine Learning4時間13 videos44 Exercises2,850 XP8,072達成証明書
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前提条件
MLOps ConceptsSupervised Learning with scikit-learn1
Moving from Research to Production
This chapter will provide you with the skills and knowledge needed to move your machine learning models from the research and development phase into a production environment. You will learn about the process of moving from a research prototype to a reliable, scalable, and maintainable system.
2
Ensuring Reproducibility
In this chapter, you’ll learn about the importance of reproducibility in machine learning, and how to ensure that your models remain reproducible and reliable over time. You’ll explore various techniques and best practices that you can use to ensure the reproducibility of your models.
3
ML in Production Environments
In Chapter 3, you’ll examine the various challenges associated with deploying machine learning models into production environments. You’ll learn about the various approaches to deploying ML models in production and strategies for monitoring and maintaining ML models in production.
4
Testing ML Pipelines
In the final chapter, you’ll learn about the various ways to test machine learning pipelines and ensure they perform as expected. You’ll discover the importance of testing ML pipelines and learn techniques for testing and validating ML pipelines.
本番環境向けのMachine Learningモデル開発
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