Train and host MindsDB models
The following section explaines how to train and host models using Amazon SageMaker console.
Create Train Job
Follow the steps below to successfully start a train job and use MindsDB to create the models: 1. Open the Amazon SageMaker console at https://console.aws.amazon.com/sagemaker/. 2. From the left panel choose Create Training Job and provide the following information * Job name * IAM role - it’s best if you provide AmazonSageMakeFullAccess IAM policy * Algorithm source - Your own algorithm container in ECR 3. Provide container ECR path * Container - the ECR registry Image URI that we have pushed * Input mode - File 4. Resource configuration - leave the default instance type and count 5. Hyperparameters - MindsDB requires to_predict column name, so it knows which column we want to predict, e.g. * Key - to_predict * Value - Class(the column in diabetes dataset) 6. Input data configuration * Channel name - training * Data source - s3 * S3 location - path to the s3 bucket where the dataset is located
7.Output data configuration - path to the s3 where the models will be saved
Create model and add the required settings: 1. Model name - must be unique 2. IAM role - it’s best if you provide AmazonSageMakeFullAccess IAM policy 3. Container input options * Provide model artifacts and inference image location * Use a single model * Location of the inference code - 846763053924.dkr.ecr.us-east-1.amazonaws.com/mindsdb_impl:latest * Location of model artifacts - path to model.tar.gz inside s3 bucket.
In the endpoint configuration, provide which models to deploy, and the hardware requirements:
- Endpoint configuration name
- Add model - select the previously created model
- Choose Create endpoint configuration.
The last step is to create endpoint and provide endpoint configuration that specify which models to deploy and the requirements:
- Endpoint name
- Attach endpoint configuration - select the previously created endpoint configuration
- Choose Create endpoint.
After finishing the above steps, SageMaker will create a new instance and start the inference code.