Machine Learning with BigQuery ML: Building Unsupervised Models

BigQuery ML 2023    |    Intermediate
  • 13 videos | 1h 41m 11s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 3 users Rating 4.3 of 3 users (3)
Unsupervised techniques such as clustering and recommendation systems can discover patterns in unlabeled data. These models extract structure in the x-variables or features present in the data. In this course, you will work with two unsupervised learning methods, clustering and recommendation systems. You will explore how clustering algorithms use only the x-variables or features in your data to group data into logical clusters. Then you will discover the basic concepts behind recommendation systems, which take in past user interactions with products and use that to recommend new products to users. Next, you will train a clustering model using k-means clustering on your data and evaluate how the clusters differ. You will use hyperparameter tuning to find the best number of clusters on your dataset. Finally, you will train a recommendations engine using collaborative filtering and use that to make movie recommendations to users based on their past preferences and the preferences of other users.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline how clustering models work and recognize their use cases
    Impute missing values and create calculated columns in dataprep
    Delete unwanted columns using dataprep
    Perform k-means clustering on data
    Perform hyperparameter tuning on a clustering model
    Explore recommendation system machine learning models
  • Load data from google cloud platform (gcp) into bigquery
    Explore and visualize data in bigquery and looker studio
    Create and use slots in bigquery
    Extract values from groups of values in bigquery
    Run a recommendation model in bigquery
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 40s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 5m 23s
    After completing this video, you will be able to outline how clustering models work and recognize their use cases. FREE ACCESS
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    3.  Loading, Exploring, and Transforming Data
    10m 38s
    Learn how to impute missing values and create calculated columns in DataPrep. FREE ACCESS
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    4.  Cleaning and Preparing Data
    8m 41s
    Find out how to delete unwanted columns using DataPrep. FREE ACCESS
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    5.  Performing K-means Clustering
    8m 44s
    In this video, discover how to perform K-means clustering on data. FREE ACCESS
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    6.  Performing Hyperparameter Tuning for Number of Clusters
    7m 29s
    In this video, you will learn how to perform hyperparameter tuning on a clustering model. FREE ACCESS
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    7.  Recommendation Systems Introduction
    7m 30s
    Find out how to explore recommendation system machine learning models. FREE ACCESS
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    8.  Creating and Loading Tables from Cloud Storage Buckets
    9m 6s
    Discover how to load data from Google Cloud Platform (GCP) into BigQuery. FREE ACCESS
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    9.  Visualizing and Exploring Movie Ratings Data
    12m 31s
    In this video, find out how to explore and visualize data in BigQuery and Looker Studio. FREE ACCESS
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    10.  Performing Slot Commitment, Reservation, and Assignment
    9m 21s
    Learn how to create and use slots in BigQuery. FREE ACCESS
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    11.  Preprocessing Data for Recommendations
    5m 50s
    Discover how to extract values from groups of values in BigQuery. FREE ACCESS
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    12.  Training a Recommendations Model and Getting Movie Recommendations
    12m 28s
    Find out how to run a recommendation model in BigQuery. FREE ACCESS
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    13.  Course Summary
    1m 50s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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