Einstein Discovery – Live Predictions with Snowflake

Einstein Discovery – Live Predictions with Snowflake
Training a machine learning model in Einstein Discovery relies upon data in CRM Analytics (CRMA) datasets. The tight coupling with CRMA datasets provides many benefits to customers in terms of data availability, feature transformations/calculations, a rich ETL layer, connections to dozens of common data sources, and so on. Once deployed to Salesforce, Einstein Discovery models ...

Einstein Discovery – Bring Your Own Model Deep Dive

Einstein Discovery – Bring Your Own Model Deep Dive
By By Einstein Discovery machine learning helps you build powerful predictive models on your data using clicks, not code. With a simple, wizard-driven interface, you have the ability to rapidly create insights and predictive models. Einstein Discovery utilizes a number of industry-standard algorithms to facilitate building models, these include: GLM (linear and logistic regression) GBM ...

Text Clustering in Einstein Discovery

Text Clustering in Einstein Discovery
It is common to build and deploy supervised machine learning models that are generally comprised of tabular datasets with numerical, categorical, and temporal (date/time) variables. Often though, there may be additional value to be gained by augmenting the model with insights derived from unstructured data (text). Some common examples of unstructured text in this context ...

Predicting the best up-sell with Einstein Discovery Multiclass models

Predicting the best up-sell with Einstein Discovery Multiclass models
Exciting news: with the Spring 22 release, Einstein Discovery supports multiclass classification predictions (Generally Available). This allows you to solve even more predictive use cases for your business with Einstein Discovery. With these Multiclass models, you can predict probable outcomes among up to 10 categories. For example, a manufacturer can predict, based on customer attributes, ...