Machine Learning with BigQuery ML: Building Unsupervised Models
BigQuery ML 2023
| Intermediate
- 13 videos | 1h 41m 11s
- Includes Assessment
- Earns a Badge
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
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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
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1m 40sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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5m 23sAfter 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 Data10m 38sLearn how to impute missing values and create calculated columns in DataPrep. FREE ACCESS
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4. Cleaning and Preparing Data8m 41sFind out how to delete unwanted columns using DataPrep. FREE ACCESS
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5. Performing K-means Clustering8m 44sIn this video, discover how to perform K-means clustering on data. FREE ACCESS
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6. Performing Hyperparameter Tuning for Number of Clusters7m 29sIn this video, you will learn how to perform hyperparameter tuning on a clustering model. FREE ACCESS
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7. Recommendation Systems Introduction7m 30sFind out how to explore recommendation system machine learning models. FREE ACCESS
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8. Creating and Loading Tables from Cloud Storage Buckets9m 6sDiscover how to load data from Google Cloud Platform (GCP) into BigQuery. FREE ACCESS
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9. Visualizing and Exploring Movie Ratings Data12m 31sIn 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 Assignment9m 21sLearn how to create and use slots in BigQuery. FREE ACCESS
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11. Preprocessing Data for Recommendations5m 50sDiscover how to extract values from groups of values in BigQuery. FREE ACCESS
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12. Training a Recommendations Model and Getting Movie Recommendations12m 28sFind out how to run a recommendation model in BigQuery. FREE ACCESS
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13. Course Summary1m 50sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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