Learn how to use Google Cloud Platform to train and deploy machine learning models for predictive analytics.
- [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.
- 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
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
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