Data Science on Google Cloud Platform: Predictive Analytics

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Kumaran Ponnambalam

39:37

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01 - Introduction

01 - Why use predictive analytics on GCP.mp4

01:08

02 - Data science modules covered.mp4

02:07

02 - 1. ML Options in GCP

01 - Cloud Dataproc.mp4

00:56

02 - Cloud ML Engine.mp4

01:37

03 - Cloud Natural Language.mp4

01:20

04 - Cloud Translation.mp4

01:17

05 - Cloud Vision.mp4

01:18

06 - Cloud Video Intelligence.mp4

01:02

07 - Cloud Dialogflow.mp4

01:14

03 - 2. Cloud ML Basics

01 - Models.mp4

00:56

02 - Model versions.mp4

00:41

03 - Jobs.mp4

00:56

04 - Predictive analytics process.mp4

01:55

04 - 3. Model Building with Cloud ML

01 - Understanding input data.mp4

01:30

02 - Build and test model locally.mp4

01:53

03 - Upload files to Cloud Storage.mp4

00:56

04 - Modify code to work with GCP.mp4

01:42

05 - Creating a training package.mp4

01:21

06 - Running training synchronously.mp4

01:39

07 - Training using jobs.mp4

03:49

05 - 4. Predictions in Cloud ML

01 - Creating a deployment model.mp4

00:38

02 - Creating a model version.mp4

02:10

03 - Creating a prediction dataset.mp4

01:10

04 - Running a prediction.mp4

01:37

06 - 5. Cloud ML Best Practices

01 - Cost control.mp4

01:17

02 - Local testing.mp4

01:12

03 - Performance monitoring.mp4

01:35

07 - Conclusion

01 - Next steps.mp4

00:41

Description

Predictive analytics use historic data to look forward, enabling organizations to make better decisions. However, making accurate predictions from big data can be an overwhelming task. Enter Google Cloud Platform (GCP), a suite of cloud-computing services that bring scalability, elasticity, and automated machine learning to predictive analytics. This course—one of a series by data scientist Kumaran Ponnambalam—shows how to apply the power of GCP to generate predictions for your business. Start off by exploring the different tools and features for predictive analytics in GCP, including Cloud Dataproc, Cloud ML Engine, and the machine learning APIs such as Cloud Translation, Cloud Vision, and Cloud Video Intelligence. Then explore learn how to build, train, and deploy models to create predictions. Plus, learn best practices for cost control, testing, and performance monitoring of predictive models.

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Data Science

Google Cloud

Kumaran Ponnambalam

Instructor's Courses

A seasoned veteran in everything data, with a reputation for delivering high performance database and SaaS applications and currently specializing in leading Big Data Science and Engineering efforts

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