- Evaluating the machine learning tools in GCP
- Understanding the predictive analytics process
- Building models
- Training models with jobs
- Building and running predictions
- Best practices for cost control, testing, and performance monitoring
Skill Level Intermediate
- [Kumaran] Businesses love predictions. Why? Because they want to predict what their customers want, and when they will need it. But, there's a lot of data here. Lots of businesses making lots of decisions. For scalability and reliability purposes, many of these prediction algorithms are built on cloud platforms, like Amazon Web Services, Google Cloud Platform, and Microsoft Azure. Expertise in these platforms is an essential skill for an IT professional.
In this course, I will show you the technologies available on Google Cloud Platform for predictive analytics that create and deploy models in the cloud to enable data signs. You'll need prior familiarity with the basics of GCP platform, as well as Python programming. So join me, Kumaram Ponnambalam, in my course. Let's explore and experience the options for predictive analytics.
Predictive Customer Analyticswith Kumaran Ponnambalam1h 37m Intermediate
1. ML Options in GCP
2. Cloud ML Basics
3. Model Building with Cloud ML
4. Predictions in Cloud ML
5. Cloud ML Best Practices
- Mark as unwatched
- Mark all as unwatched
Are you sure you want to mark all the videos in this course as unwatched?
This will not affect your course history, your reports, or your certificates of completion for this course.Cancel
Take notes with your new membership!
Type in the entry box, then click Enter to save your note.
1:30Press on any video thumbnail to jump immediately to the timecode shown.
Notes are saved with you account but can also be exported as plain text, MS Word, PDF, Google Doc, or Evernote.