Continuous Integration for Data Science Projects

Yash GadodiaYash Gadodia
1 min read

  • Importance of CI in data science and machine learning.

  • Best practices for managing datasets and model versions.

  • Tools for automating testing and deployment of ML models.

  • How to integrate CI/CD with data pipelines.

  • Case studies of successful CI for data science teams.

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Written by

Yash Gadodia
Yash Gadodia

Ambitious Cloud Computing postgraduate with hands-on experience in AWS, Azure, and DevOps, specializing in cloud infrastructure management, security, and cost optimization. Proven ability to enhance security posture and automate solutions for scalable, efficient cloud operations.