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Introduction to Vertex Forecasting and Time Series in Practice

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Introduction to Vertex Forecasting and Time Series in Practice

magic_button Machine Learning Models Machine Learning Model Training Machine Learning Pipeline
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24 hours Intermediate universal_currency_alt 11 Credits

This course is an introduction to building forecasting solutions with Google Cloud. You start with sequence models and time series foundations. You then walk through an end-to-end workflow: from data preparation to model development and deployment with Vertex AI. Finally, you learn the lessons and tips from a retail use case and apply the knowledge by building your own forecasting models.

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Course Info
Objectives
  • Understand the key concepts and the applications of a sequence model, time series, and forecasting.
  • Identify the options to develop a forecasting model on Google Cloud.
  • Describe the workflow to develop a forecasting model by using Vertex AI.
  • Prepare data (including ingestion and feature engineering) by using BigQuery and Vertex managed datasets.
  • Train a forecasting model and evaluate the performance by using AutoML.
  • Deploy and monitor a forecasting model by using Vertex AI Pipelines.
  • Build a forecasting solution from end-to-end using a retail dataset.
Prerequisites
Having one or more of the following: - Basic knowledge of Python syntax - Basic understanding of machine learning models - Prior experience building machine learning solutions on Google Cloud
Audience
Professional data analysts, data scientists, and ML engineers who want to build end-to-end high performance forecasting solutions on Google Cloud and add automation to the workflow.
Available languages
English
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