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Machine Learning in the Enterprise

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Duration

2h 12m

level

Beginner

Course Creator

Google Cloud

Last Updated

19-Aug-22

This course encompasses a real-world practical approach to the ML Workflow: a case study approach that presents an ML team faced with several ML business requirements and use cases.

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This course encompasses a real-world practical approach to the ML Workflow: a case study approach that presents an ML team faced with several ML business requirements and use cases. This team must understand the tools required for data management and governance and consider the best approach for data preprocessing: from providing an overview of Dataflow and Dataprep to using BigQuery for preprocessing tasks. The team is presented with three options to build machine learning models for two specific use cases. This course explains why the team would use AutoML, BigQuery ML, or custom training to achieve their objectives. A deeper dive into custom training is presented in this course. We describe custom training requirements from training code structure, storage, and loading large datasets to exporting a trained model. You will build a custom training machine learning model, which allows you to build a container image with little knowledge of Docker. The case study team examines hyperparameter tuning using Vertex Vizier and how it can be used to improve model performance. To understand more about model improvement, we dive into a bit of theory: we discuss regularization, dealing with sparsity, and many other essential concepts and principles. We end with an overview of prediction and model monitoring and how Vertex AI can be used to manage ML models
Author Name: Google Cloud
Author Description:
Google Cloud can help solve your toughest problems and grow your business. With Google Cloud, their infrastructure is your infrastructure. Their tools are your tools. And their innovations are your innovations.

Table of Contents

  • Introduction
    1min
  • Understanding the ML Enterprise Workflow
    6mins
  • Data in the Enterprise
    33mins
  • Science of Machine Learning and Custom Training
    36mins
  • Vertex Vizier Hyperparameter Tuning
    17mins
  • Prediction and Model Monitoring Using Vertex AI
    16mins
  • Vertex AI Pipelines
    5mins
  • Best Practices for ML Development
    11mins
  • Course Summary
    0mins
  • Series Summary
    3mins

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Machine Learning in the Enterprise
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