jeff-hernandez
Predicting Consumer Spending with AutoML
Predictive Maintenance with AutoML
Demand Forecasting with AutoML
Easily define prediction tasks for ML
Make the Most of Machine Learning
Tap the predictive power of machine learning
Building Better Training Examples
Label Generation for ML
A cross-domain framework for labeling data
Generate training data for supervised learning
Build training examples without manually labeling
Using automation to label time-driven data
Structuring the labeling process for supervised learning
Automated Data Labeling
Labeling data more effectively for supervised learning
Re:Snorkel AI: Putting Data First in ML Development
on Thursday July 16, 2020 @01:05PM (#23861041)
Yes, you can represent the labeling function as a class and use its methods to represent each label individually.
Re:Snorkel AI: Putting Data First in ML Development
on Thursday July 16, 2020 @11:53AM (#23860236)
Yes, you can represent the labeling function as a class and use its methods to represent each label individually.
Compose: An ML tool for labeling data
Re:Compose: An ML tool for labeling data
on Thursday July 16, 2020 @10:13AM (#23859166)
Compose lets you structure the labeling process by parameterizing prediction problems and integrates easily with Featuretools which automates feature engineering. Definitely worth checking out!
Re:Snorkel AI: Putting Data First in ML Development
on Thursday July 16, 2020 @09:55AM (#23859014)
As another option, Compose is a ML tool for labeling data. It structures the labeling process and integrates easily with Featuretools which automates feature engineering. Definitely worth checking out!
[1] https://github.com/FeatureLabs/compose [2] https://github.com/FeatureLabs/featuretools