A deep dive into AI as a DevOps data- expert

AI services are a type of cloud service that provides access to pre-trained models and algorithms, for use in ML and other AI applications. From a DevOps and infrastructure point of view, AI services can be a powerful tool to accelerate the development and deployment of AI applications.

Here are some examples of AI services and how they can be used.

Amazon SageMaker

Amazon SageMaker is a fully managed service that provides developers and data scientists with the ability to build, train, and deploy ML models at scale.

Here is an example of using Amazon SageMaker to train an ML model:

PYTHON

import boto3
import sagemaker
# create a SageMaker session
session = sagemaker.Session()
# create an S3 bucket for storing training data
bucket_name = 'my-bucket'
bucket = session.default_bucket()
s3_input = sagemaker.s3_input(s3_data=f's3://{bucket_name}/training_data.csv', content_type='csv')
# create a...