This page is for Kumo Engine.
Browse the notebooks and Python examples in the Kumo Engine examples repository. Choose an example below and follow its setup and data prerequisites.
Examples are grouped by industry, with deployment and scope listed for each workflow. Entries marked Commented preview contain demonstrations that are not runnable with the supported package API.
Cross-industry
Notebooks
| Example | Deployment | Scope |
|---|---|---|
| Build a custom training table | Local | Focused workflow |
| Choose a static or temporal query | Local | Focused workflow |
| Choose the customers to score | Databricks | Focused workflow |
| Preview graph visualization | Local | Commented preview |
SDK code examples
Energy
SDK code examples
| Example | Deployment | Scope |
|---|---|---|
| Regress hourly transformer oil temperature from the public ETT series | Local | Model workflow |
Financial services
Notebooks
| Example | Deployment | Scope |
|---|---|---|
| Predict reported transaction fraud on Databricks | Databricks | Model workflow |
| Screen accounts for money muling | Databricks | Model workflow |
| Screen synthetic transactions for review | Local | Synthetic binary classification |
| Detect money mule activity in synthetic accounts | Local | Synthetic account classification with a baseline and new-account scoring |
SDK code examples
| Example | Deployment | Scope |
|---|---|---|
| Classify loan status from the eight-table public Financial relational dataset | Local | Model workflow |
| Predict Home Credit default risk from seven public competition tables | Local | Model workflow |
Healthcare
Notebooks
| Example | Deployment | Scope |
|---|---|---|
| Predict appointment attendance in the next 30 days | Local | Synthetic temporal binary classification |
Hospitality
SDK code examples
| Example | Deployment | Scope |
|---|---|---|
| Classify the booking destination of Airbnb new users using sessions and demographics | Local | Model workflow |
| Forecast three daily interaction counts for each user | Local | Model workflow |
| Predict each user’s interaction count for the next day | Local | Model workflow |
| Predict whether each user will interact in the next day | Local | Model workflow |
| Predict which interaction types each user will have in the next day | Local | Model workflow |
| Rank restaurant relationships without a future prediction window | Local | Model workflow |
| Rank restaurants each user may interact with in the next day | Local | Model workflow |
| Recommend available recipes from authorized recipe/order tables | Local | Model workflow |
| Reload a trusted restaurant model and score its unchanged original snapshot | Local | Model workflow |
| Train a small restaurant model and score twenty held-out cuisine labels | Local | Model workflow |
Media and entertainment
Notebooks
| Example | Deployment | Scope |
|---|---|---|
| Predict low ratings for movies on Snowflake | Snowflake | Model workflow |
| Predict the content formats each subscriber will use | Local | Synthetic multilabel classification |
SDK code examples
| Example | Deployment | Scope |
|---|---|---|
| Predict a movie’s average rating during the next twelve months | Local | Model workflow |
| Recommend Stack posts a user will comment on over the next two years | Local | Model workflow |
| Regress MovieLens 1M ratings for user/movie pairs at their rating times | Local | Model workflow |
Retail
Notebooks
| Example | Deployment | Scope |
|---|---|---|
| Classify store products into a category | Local | Synthetic multiclass classification |
| Explore Kumo Engine tasks with TPC-H on Snowflake | Snowflake | Model workflow |
| Kumo Engine task examples with AdventureWorks in Google Colab | Colab | Model workflow |
| Kumo Engine task examples with TPC-H on Databricks | Databricks | Model workflow |
| Predict repeat orders with AdventureWorks | Snowflake | Model workflow |
| Predict repeat orders with AdventureWorks on Databricks | Databricks | Model workflow |
| Recommend products from synthetic purchase histories | Local | Synthetic temporal recommendations |
| Tag store products with every applicable label | Local | Synthetic multilabel classification |
SDK code examples
Science
SDK code examples
| Example | Deployment | Scope |
|---|---|---|
| Forecast monthly sunspot counts from the public SILSO series | Local | Model workflow |