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title: Create Predictive AI Models From Scratch
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version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_ai_ec_create_model.md
canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_ai_ec_create_model.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 8024daa9910f73d0c160d7f38775e508c51551c3e2302516ca39dcb7745c6775
description: Create models to analyze your data and get AI powered predictions based on machine learning. Learn about supported use cases and ethical model building. Then, follow the steps to create a model and evaluate model quality.
products:
  - Data 360
release: "264"
---
# Create Predictive AI Models From Scratch

Create models to analyze your data and get AI powered predictions based on machine learning. Learn about supported use cases and ethical model building. Then, follow the steps to create a model and evaluate model quality.

### Required Editions

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small edition"><colgroup><col></colgroup><tbody><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;">Available in: <strong>All Editions</strong> supported by Data 360. See <a href="https://help.salesforce.com/s/articleView?id=data.c360_a_dc_editions.htm&amp;language=en_US" target="_blank">Data 360 edition availability</a>.</td></tr></tbody></table>

- **[Supported Predictive Model Types](https://help.salesforce.com/s/articleView?id=data.c360_a_ai_ec_use_cases.htm&release=264.0.0&type=5)**  
    Predictive models address common business use cases.
- **[Algorithms and Loss Functions](https://help.salesforce.com/s/articleView?id=data.c360_a_ai_predictive_algorithms_loss_functions.htm&release=264.0.0&type=5)**  
    Predictive models analyze historical data to discover patterns and relationships that predict future outcomes. Model Builder provides algorithms for binary, multiclass, and regression models with configurable training settings. When you train a predictive model with a numeric outcome, loss functions measure how far predicted values are from actual values. During training, the model minimizes this loss to improve overall prediction accuracy. The selected loss function determines the types of prediction errors that the model prioritizes.These settings enable you to generate predictions that drive business decisions and surface customer insights.
- **[Design Ethical AI Models](https://help.salesforce.com/s/articleView?id=data.c360_a_ai_ec_ethical_model_building.htm&release=264.0.0&type=5)**  
    Salesforce offers guidance to help you practice ethical use of artificial intelligence (AI) in your business.
- **[Prepare Your Training Data](https://help.salesforce.com/s/articleView?id=data.c360_a_ai_predictive_prep_data.htm&release=264.0.0&type=5)**  
    Effective data preparation is the key to getting great results with your predictive model. Harness the power of data integration in Data 360. Load and transform data from one or more data sources into a data model object (DMO) with optimized training data. You can pull data from Salesforce and external sources. You can also use third-party tools and utilities to further expedite data cleansing and wrangling tasks.
- **[Create a Model from Scratch](https://help.salesforce.com/s/articleView?id=data.c360_a_ai_ec_create_model_steps.htm&release=264.0.0&type=5)**  
    Create a model that uses historical data to predict future outcomes. Select and structure your data source and define the desired outcome. Then train the model to reveal predictive inferences and insights by using AI, machine learning, and statistical analysis.
- **[Improve Predictive Models](https://help.salesforce.com/s/articleView?id=data.c360_a_ai_predictive_model_quality.htm&release=264.0.0&type=5)**  
    Model quality is a critical success factor in predictive AI solutions. AI Models (formerly Einstein Studio) supports continuous, iterative improvement for predictive models. Measure model quality in production over time. Use quality alerts to identify and address areas for improvement. Experiment with new model versions. Efforts to improve model quality result in better business outcomes.
- **[Evaluate Model Quality](https://help.salesforce.com/s/articleView?id=data.c360_a_ai_ec_evaluate_model_quality.htm&release=264.0.0&type=5)**  
    Use training metrics to evaluate the model’s ability to predict an outcome and determine whether it’s ready to activate. Training metrics provide information about how effectively the model understands patterns and relationships within the training data, and indicates its predictive efficacy.