Machine Learning with BigQuery ML: Building Regression Models

BigQuery ML 2023    |    Beginner
  • 14 videos | 2h 4m 17s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 7 users Rating 4.3 of 7 users (7)
BigQuery is a flagship product on the Google Cloud Platform which allows you to build and train machine learning (ML) models using simple SQL queries. BigQuery has support for a range of supervised and unsupervised machine learning models that can be trained on data stored in BigQuery. In this course, you will be introduced to BigQuery on the Google Cloud Platform and set up a GCP trial account that allows you to work with BigQuery to train ML models. You will then review some machine learning basics and dig a little deeper into regression models. Next, you will create datasets and tables in BigQuery and upload your data to the cloud. You will visualize and explore your data using Looker Studio and prepare and clean your data using DataPrep. Finally, you will train regression models using linear regression, gradient-boosted trees, and the random forest model and evaluate and compare the performance of these models on your test data.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline how bigquery and bigquery ml work
    Differentiate between the different kinds of machine learning (ml) models
    Set up google cloud platform (gcp) and bigquery
    Outline how regression models work and identify their use cases
    Create and load data into a bigquery table
    Visualize bigquery data in looker studio
  • Process data using dataprep
    Process and split data for training and test
    Train a linear regression model
    Evaluate and understand an ml model
    Build a boosted tree regression model
    Build a random forest regression model
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 47s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 12m 31s
    After completing this video, you will be able to outline how BigQuery and BigQuery ML work. FREE ACCESS
  • Locked
    3.  Supervised and Unsupervised Machine Learning (ML)
    7m 42s
    In this video, find out how to differentiate between the different kinds of machine learning (ML) models. FREE ACCESS
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    4.  Creating a Google Cloud Platform (GCP) Account and Accessing BigQuery
    10m 56s
    Learn how to set up Google Cloud Platform (GCP) and BigQuery. FREE ACCESS
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    5.  Regression Model Introduction
    5m 38s
    Upon completion of this video, you will be able to outline how regression models work and identify their use cases. FREE ACCESS
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    6.  Creating a Dataset Table and Loading Data
    12m 49s
    Find out how to create and load data into a BigQuery table. FREE ACCESS
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    7.  Exploring and Visualizing Data with Looker Studio
    10m 34s
    In this video, you will learn how to visualize BigQuery data in Looker Studio. FREE ACCESS
  • Locked
    8.  Processing Data with DataPrep - I
    11m 1s
    In this video, discover how to process data using DataPrep. FREE ACCESS
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    9.  Processing Data with DataPrep - II
    10m 21s
    Learn how to process and split data for training and test. FREE ACCESS
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    10.  Training and Evaluating a Linear Regression Model
    11m 15s
    Find out how to train a linear regression model. FREE ACCESS
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    11.  Viewing and Evaluating and ML Model
    8m 41s
    In this video, you will learn how to evaluate and understand an ML model. FREE ACCESS
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    12.  Training and Evaluating a Boosted Tree Regression Model
    10m 35s
    Discover how to build a boosted tree regression model. FREE ACCESS
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    13.  Training and Evaluating a Random Forest Model
    8m 24s
    Discover how to build a random forest regression model. FREE ACCESS
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    14.  Course Summary
    2m 2s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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