In this video, set up Cloud Storage and upload source data into Cloud Storage.
- [Instructor] Cloud ML only works off source files.…They're not available to cloud storage.…Hence, we need to upload all input files,…whether it's for model building or for predictions…into a cloud storage bucket.…To do this, let's go to the cloud storage dashboard.…We already have a bucket called exercise-lil.…We will create a data tree called predictive under it…by using the create folder option.…Then, we can upload the web-browsing-data.csv file…into that folder, by using the Upload files command.…
The file is now uploaded into the bucket.…We can access this import file now using the URL…GS://exercise-lil/predictive/web-browsing-data.csv.…
- 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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