AWS Machine Learning

DECEMBER 21, 2022

Amazon SageMaker Feature Store is a purpose-built feature management solution that helps data scientists and ML engineers securely store, discover, and share curated data used in training and prediction workflows. In this example, we ingest records using the FeatureGroup.ingest() API, which ingests records from a Pandas DataFrame.

Scripts 74

Scripts Engineering APIs Big data 74

AWS Machine Learning

JULY 24, 2023

If the model changes on the server side, the client has to know and change its API call to the new endpoint accordingly. Clone the Github repository The GitHub repo provides all the scripts necessary to deploy models using FastAPI on NeuronCores on AWS Inferentia instances. code as the entry point. compiled-model-bs-{batch_size}.pt')

Scripts 74

Scripts APIs Engineering Best practices 74

AWS Machine Learning

NOVEMBER 26, 2023

Gartner predicts that “by 2026, more than 80% of enterprises will have used generative AI APIs or models, or deployed generative AI-enabled applications in production environments, up from less than 5% in 2023.” However, scripting appealing subject lines can often be tedious and time-consuming.

Personalization 104

Personalization Customer Experience APIs Entertainment 104

COPC

OCTOBER 26, 2023

Crafting LLM AI Assistants: Roles, Process and Timelines Using the latest AI may seem as easy as developers using APIs in commercial LLM options like OpenAI. But it’s much more than enlisting engineers to call LLM APIs. Team: Beyond engineers, various roles contribute to the AI assistant’s creation.

Technology 77

Technology Customer Experience APIs Consulting 77

AWS Machine Learning

FEBRUARY 13, 2024

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

Accountability 106

Accountability Government Engineering Scripts 106

AWS Machine Learning

AUGUST 4, 2023

When a version of the model in the Amazon SageMaker Model Registry is approved, the endpoint is exposed as an API with Amazon API Gateway using a custom Salesforce JSON Web Token (JWT) authorizer. frameworks to restrict client access to your APIs. For API Name , leave as default (it’s automatically populated).

APIs 79

APIs Scripts Management Accountability 79

AWS Machine Learning

NOVEMBER 21, 2023

REGION.amazonaws.com/sagemaker-matlab-training-r2023a:latest Open MATLAB and open the live script called PumpFaultClassificationMATLABSageMaker.mlx in folder examples/PumpFaultClassification. The training function should be provided at the bottom of the MATLAB live script. amazonaws.com docker push ACCOUNT.dkr.ecr.

Engineering 88

Engineering APIs Scripts Automotive 88

AWS Machine Learning

OCTOBER 2, 2023

For this we use AWS Step Functions , a serverless workflow service that provides us with API integrations to quickly orchestrate and visualize the steps in our workflow. Use the scripts created in step one as part of the processing and training steps. We started by creating command line scripts from the experiment code.

Scripts 94

Scripts Construction Engineering APIs 94

AWS Machine Learning

OCTOBER 25, 2022

Model weights are available via scripts in the GitHub repository , and the MSAs are hosted by the Registry of Open Data on AWS (RODA). We use aws-do-eks , an open-source project that provides a large collection of easy-to-use and configurable scripts and tools to enable you to provision EKS clusters and run your inference.

APIs 77

APIs Scripts Banking Engineering 77

AWS Machine Learning

MARCH 23, 2023

Applications and services can call the deployed endpoint directly or through a deployed serverless Amazon API Gateway architecture. To learn more about real-time endpoint architectural best practices, refer to Creating a machine learning-powered REST API with Amazon API Gateway mapping templates and Amazon SageMaker.

Scripts 97

Scripts APIs Government Analytics 97

AWS Machine Learning

MAY 31, 2023

Once configured, the Python SDK automatically inherits these values and propagates them to the underlying SageMaker API calls such as CreateProcessingJob() , CreateTrainingJob() , and CreateEndpointConfig() , with no additional actions needed. Additionally, each API call can have its own configurations.

APIs 80

APIs Scripts Accountability Enterprise 80

AWS Machine Learning

JUNE 15, 2022

If you just want to read about this feature without running it yourself, you can refer to the Python script facet-search-query.py Set up the infrastructure and run the Python script to query the Amazon Kendra index. For convenience, all the steps are included in one Python script. Prerequisites. Access to AWS CloudShell.

APIs 72

APIs Scripts Technology Engineering 72

AWS Machine Learning

SEPTEMBER 28, 2022

Data scientists sometimes train models locally using their IDE and either ship those models to the ML engineering team for deployment or just run predictions locally on powerful machines. Prepare your trained model and inference script. pth,pkl, and so on) and an inference script. Solution overview.

Scripts 75

Scripts APIs Engineering Consulting 75

AWS Machine Learning

FEBRUARY 15, 2023

You can fine-tune and deploy JumpStart models using the UI in Amazon SageMaker Studio or using the SageMaker Python SDK extension for JumpStart APIs. This post focuses on how we can implement MLOps with JumpStart models using JumpStart APIs, Amazon SageMaker Pipelines , and Amazon SageMaker Projects. sm_client = boto3.client("sagemaker")

Scripts 85

Scripts APIs Engineering Enterprise 85

AWS Machine Learning

APRIL 18, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Scripts 97

Scripts Best practices Engineering Accountability 97

VirtualPBX

NOVEMBER 5, 2020

Using The VirtualPBX API to Assist. You can also manage your hooks outside of the VirtualPBX web interface by taking advantage of our API. The VirtualPBX API lets you manage a number of types of data that exist within your phone plan. The VirtualPBX API lets you manage a number of types of data that exist within your phone plan.

Marketing 98

Marketing APIs voip Scripts 98

AWS Machine Learning

JULY 5, 2022

Data Wrangler is a capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications via a visual interface. LCC scripts are triggered by Studio lifecycle events, such as starting a new Studio notebook. Apply the script (see below). Solution overview.

Scripts 81

Scripts Engineering APIs Consulting 81

AWS Machine Learning

NOVEMBER 1, 2022

Data scientists need to only provide a tabular dataset and select the target column to predict, and Autopilot automatically infers the problem type, performs data preprocessing and feature engineering, selects the algorithms and training mode, and explores different configurations to find the best ML model. script creates an Autopilot job.

Scripts 78

Scripts APIs Metrics Engineering 78

AWS Machine Learning

SEPTEMBER 28, 2022

Amazon SageMaker Pipelines allows data scientists and machine learning (ML) engineers to automate training workflows, which helps you create a repeatable process to orchestrate model development steps for rapid experimentation and model retraining. Define a processing script and processing step. and xlrd >=1.0.0 Model building.

Scripts 71

Scripts Engineering APIs Management 71

AWS Machine Learning

MAY 19, 2023

The DescribeForMe web app invokes the backend AI services by sending the Amazon S3 object Key in the payload to Amazon API Gateway Amazon API Gateway instantiates an AWS Step Functions workflow. A pre-signed URL with the location of the audio file stored in Amazon S3 is sent back to the user’s browser through Amazon API Gateway.

APIs 90

APIs Scripts Engineering Best practices 90

AWS Machine Learning

DECEMBER 29, 2022

Users can also interact with data with ODBC, JDBC, or the Amazon Redshift Data API. This blog focuses on the Rstudio on Amazon SageMaker language, with business analysts, data engineers, data scientists, and all developers that use the R Language and Amazon Redshift, as the target audience. Prerequisites.

APIs 106

APIs Engineering Analytics Scripts 106

AWS Machine Learning

OCTOBER 4, 2022

Developers usually test their processing and training scripts locally, but the pipelines themselves are typically tested in the cloud. From a very high level, the ML lifecycle consists of many different parts, but the building of an ML model usually consists of the following general steps: Data cleansing and preparation (feature engineering).

Scripts 73

Scripts Engineering Management APIs 73

AWS Machine Learning

DECEMBER 19, 2022

We walk through an end-to-end example, from loading the Faster R-CNN object detection model weights, to saving them to an Amazon Simple Storage Service (Amazon S3) bucket, and to writing an entrypoint file and understanding the key parameters in the PyTorchModel API. Step 4: Building ML model inference scripts. Step 1: Setup.

Automotive 76

Automotive APIs Engineering Scripts 76

AWS Machine Learning

MAY 25, 2023

We implement the RAG functionality inside an AWS Lambda function with Amazon API Gateway to handle routing all requests to the Lambda. We implement a chatbot application in Streamlit which invokes the function via the API Gateway and the function does a similarity search in the OpenSearch Service index for the embeddings of user question.

APIs 78

APIs Enterprise Accountability Chatbots 78

AWS Machine Learning

MARCH 21, 2023

It contains over 300 built-in data transformation steps to aid with feature engineering, normalization, and cleansing to transform your data without having to write any code. We use the get_file API function to pull files from the CodeCommit repository into the Data Wrangler environment. Choose Preview.

Scripts 63

Scripts Banking APIs Best practices 63

AWS Machine Learning

MAY 23, 2023

The web application interacts with the models via Amazon API Gateway and AWS Lambda functions as shown in the following diagram. API Gateway provides the web application and other clients a standard RESTful interface, while shielding the Lambda functions that interface with the model. Clone and set up the AWS CDK application.

APIs 93

APIs Accountability Construction Management 93

AWS Machine Learning

AUGUST 30, 2023

In order to run inference through SageMaker API, make sure to pass the Predictor class. pre_trained_model = Model( image_uri=deploy_image_uri, model_data=pre_trained_model_uri, role=aws_role, predictor_cls=Predictor, name=pre_trained_name, env=large_model_env, ) # Deploy the pre-trained model.

Healthcare 113

Healthcare APIs Scripts Metrics 113

AWS Machine Learning

MAY 17, 2023

The events trigger Lambda functions to make API calls to Amazon Transcribe and invoke the real-time endpoint hosting the Flan T5 XL model. Once created, the endpoint can be invoked with the InvokeEndpoint API. The solution can be deployed with other FMs available on JumpStart. Download the generated text file to view the transcription.

APIs 71

APIs Scripts Engineering Management 71

AWS Machine Learning

AUGUST 3, 2023

Finally, we show how you can integrate this car pose detection solution into your existing web application using services like Amazon API Gateway and AWS Amplify. For each option, we host an AWS Lambda function behind an API Gateway that is exposed to our mock application. iterdir(): if p_file.suffix == ".pth":

APIs 64

APIs Scripts Engineering Technical Support 64

AWS Machine Learning

MARCH 20, 2023

Use the supplied Python scripts for quantization. Run the provided Python test scripts to invoke the SageMaker endpoint for both INT8 and FP32 versions. Quantizing the model in PyTorch is possible with a few APIs from Intel PyTorch extensions. py scripts for testing. times greater with INT8 quantization.

Calibration 79

Calibration Scripts Benchmark APIs 79

AWS Machine Learning

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Best practices 124

Best practices Government Engineering Accountability 124

AWS Machine Learning

FEBRUARY 13, 2023

An administrator can run the AWS CDK script provided in the GitHub repo via the AWS Management Console or in the terminal after loading the code in their environment. Choose Open Jupyter to start running the Python script for performing the log analysis. The steps are as follows: Open AWS Cloud9 on the console.

Scripts 74

Scripts Best practices Transportation Construction 74

AWS Machine Learning

JULY 29, 2022

For data processing and feature engineering, they can run SageMaker processing jobs with an Athena data source and output results back to Amazon Simple Storage Service (Amazon S3). Now that you have a subset of the data as a dataframe, you can start exploring the data and see what feature engineering updates are needed for model training.

Scripts 72

Scripts Analytics Accountability Engineering 72

AWS Machine Learning

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

Engineering 104

Engineering Accountability Construction APIs 104

AWS Machine Learning

AUGUST 14, 2023

Prompt engineering for zero-shot and few-shot NLP tasks on BLOOM models Prompt engineering deals with creating high-quality prompts to guide the model towards the desired responses. Prompt engineering can greatly improve the performance of zero-shot and few-shot learning models. Question: When was NLP Cloud founded?

Engineering 72

Engineering APIs Chatbots Scripts 72

AWS Machine Learning

NOVEMBER 16, 2022

Workload accounts – These are commonly QA and prod environments where software engineers are able to build applications to consume the ML model. You can use Boto3 APIs as shown the following example, or you can use the AWS Management Console to create the model package. Sreedevi Srinivasan is an engineering leader in AWS SageMaker.

Accountability 83

Accountability Best practices Scripts Engineering 83

AWS Machine Learning

NOVEMBER 21, 2022

This notebook demonstrates how to use the JumpStart API for text classification. To run inference on this model, we first need to download the inference container ( deploy_image_uri ), inference script ( deploy_source_uri ), and pre-trained model ( base_model_uri ). Text classification.

Scripts 72

Scripts Metrics APIs Healthcare 72