AWS Machine Learning

AUGUST 21, 2024

We also explore best practices for optimizing your batch inference workflows on Amazon Bedrock, helping you maximize the value of your data across different use cases and industries. Solution overview The batch inference feature in Amazon Bedrock provides a scalable solution for processing large volumes of data across various domains.

Call Center 115

Call Center APIs Engineering Accountability 115

AWS Machine Learning

SEPTEMBER 6, 2023

For this example, we use train.cc_casebooks.jsonl.xz Prerequisites Before getting started, make sure you have the following prerequisites: An AWS account. For more information, refer to Amazon SageMaker Identity-Based Policy Examples. This dataset is a large corpus of legal and administrative data. within this repository.

Enterprise 128

Enterprise APIs Real estate Construction 128

AWS Machine Learning

SEPTEMBER 18, 2024

The following is an example of a synthetically generated offering for the construction industry: OneCompany Consulting Construction Consulting Services Offerings Introduction OneCompany Consulting is a premier construction consulting firm dedicated to. Our examples were manually created only for high-level guidance for simplicity.

Personalization 128

Personalization Construction Consulting Consulting 128

AWS Machine Learning

DECEMBER 19, 2023

Customers can configure an AWS account, the repository, the model, the data used, the pipeline name, the training framework, the number of instances to use for training, the inference framework, and any pre- and post-processing steps and several other configurations to check the model quality, bias, and explainability.

Analytics 132

Analytics Engineering Government Best practices 132

AWS Machine Learning

NOVEMBER 1, 2022

According to a Forbes survey , there is widespread consensus among ML practitioners that data preparation accounts for approximately 80% of the time spent in developing a viable ML model. To demonstrate the orchestrated workflow, we use an example dataset regarding diabetic patient readmission. Prerequisites. An S3 bucket.

Engineering 98

Engineering APIs Accountability industry solution 98

AWS Machine Learning

DECEMBER 1, 2022

This post also provides an example end-to-end notebook and GitHub repository that demonstrates SageMaker geospatial capabilities, including ML-based farm field segmentation and pre-trained geospatial models for agriculture. This example user interface depicts common geospatial data overlays consumed by farmers and agricultural stakeholders.

APIs 98

APIs Analytics Engineering Technology 98

AWS Machine Learning

APRIL 25, 2023

We include an example of how to use the decorator function and the associated settings later in this post. In the following example code, we run a simple divide function as a SageMaker Training job: import boto3 import sagemaker from sagemaker.remote_function import remote sm_session = sagemaker.Session(boto_session=boto3.session.Session(region_name="us-west-2"))

Engineering 101

Engineering Metrics Construction Management 101