-
Tech preview: ML project plan 1 min
-
Step 4 - Algorithm and framework selection 3 min
-
Step 5 - Model training and validation 5 min
-
Step 6 - Implementation to production and monitoring 7 min
-
Quiz
Machine Learning Pipeline: Implement
Get familiar with the second phase of the machine learning workflow process: implementation, and the importance of on-going project monitoring.
As covered in the previous courses, the machine learning workflow presents a repeatable process of six steps that can be followed for any machine learning project. It shows how companies are implementing ML to maximize their business results and discusses the importance of on-going project monitoring. This course focuses on the second, implementation phase, of the machine learning workflow.
What's covered
- Project plan overview
- Step 4: Algorithm and framework selection
- Step 5: Model training and validation
- Step 6: Implementation to production and monitoring
- Quiz
For more information on how HPE manages, uses and protects your information please refer to HPE Privacy Statement. You can always withdraw or modify your consent to receive marketing communication from HPE. This can be done by using the opt-out and preference mechanism at the bottom of our email marketing communication or by following this link.
×