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Solve Kaggle’s House Prices Advanced Regression w/ Kubeflow, Kale and MLOps

The Kaggle House Prices problem is a popular Data Science topic. In this course, you will explore how to solve this problem with Kubeflow. In addition, you’ll learn how the work you are doing is the foundation for an effective and self-sustainable MLOps culture and platform solution that you can undertake at your enterprise. Earn your certificate and share it on LinkedIn to show your continued progression with Kaggle, Kubeflow, and MLOps.

  • Course Number

    Course
  • Self-Paced

About This Course

This course is approximately 90 minutes long.

In this course, you will:

  • Learn about Kaggle.
  • Learn about Kubeflow.
  • Learn about MLOps.
  • Use Jupyter Notebooks in Kubeflow to review the Kaggle House Prices Solution
  • Use Kale to convert a Jupyter Notebook into a Kubeflow Pipeline.
  • Relate the activities in this course back to the core tenets of MLOps.

Instructor Led Option

If you would prefer to take the course live, this course is available on a monthly basis with an instructor. If this is your preference, navigate and sign up here. here .

Certificate of Completion

At the end of this course do not close out the course without earning and sharing your certificate! This certificate can be shared on Linkedin to showcase your new skills.

Requirements

Arrikto Academy assumes that you have familiarity with popular Data Science concepts and have used some of these philosophies in practice.

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