AWS Machine Learning

JANUARY 8, 2024

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). In this post, we focus on processing a large collection of documents into raw text files and storing them in Amazon S3.

Scripts 93

Scripts Construction APIs Healthcare 93

AWS Machine Learning

DECEMBER 21, 2022

A new optional parameter TableFormat can be set either interactively using Amazon SageMaker Studio or through code using the API or the SDK. The following code snippet shows you how to create a feature group using the Iceberg format and FeatureGroup.create API of the SageMaker SDK. You can find the sample script in GitHub.

Scripts 79

Scripts Engineering APIs Big data 79

AWS Machine Learning

AUGUST 30, 2023

Radiology reports are comprehensive, lengthy documents that describe and interpret the results of a radiological imaging examination. For a quantitative analysis of the generated impression, we use ROUGE (Recall-Oriented Understudy for Gisting Evaluation), the most commonly used metric for evaluating summarization.

Healthcare 119

Healthcare APIs Scripts Metrics 119

AWS Machine Learning

MAY 22, 2023

You can monitor performance metrics such as training and validation loss using Amazon CloudWatch during training. Note that you need to pass the Predictor class when deploying model through the Model class to be able to run inference through the SageMaker API.

APIs 96

APIs Scripts Metrics Accountability 96

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. To access the code and documentation, refer to the GitHub repo. Quantizing the model in PyTorch is possible with a few APIs from Intel PyTorch extensions.

Calibration 84

Calibration Scripts Benchmark APIs 84

AWS Machine Learning

AUGUST 3, 2022

Amazon Comprehend is a natural-language processing (NLP) service you can use to automatically extract entities, key phrases, language, sentiments, and other insights from documents. All you need to do is load your dataset of documents and annotations, and use the Amazon Comprehend console, AWS CLI, or APIs to create the model.

Benchmark 72

Benchmark APIs Metrics Scripts 72

AWS Machine Learning

APRIL 19, 2023

Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts. Ideally, we instead want to load the model PyTorch scripts, extract the features from model input, and run model inference entirely in Java. However, a few issues came with this solution.

Engineering 81

Engineering APIs Scripts Education 81

AWS Machine Learning

AUGUST 14, 2023

Enterprise search is a critical component of organizational efficiency through document digitization and knowledge management. Enterprise search covers storing documents such as digital files, indexing the documents for search, and providing relevant results based on user queries. Initialize DocumentStore and index documents.

Enterprise 74

Enterprise Scripts Best practices Analytics 74

AWS Machine Learning

DECEMBER 6, 2023

Such data often lacks the specialized knowledge contained in internal documents available in modern businesses, which is typically needed to get accurate answers in domains such as pharmaceutical research, financial investigation, and customer support. For example, imagine that you are planning next year’s strategy of an investment company.

Analytics 109

Analytics APIs Engineering Construction 109

AWS Machine Learning

NOVEMBER 16, 2022

Enhanced monitoring and observability for ML workloads including Amazon EKS, Kubeflow metrics, and application logs using Prometheus, Grafana, and Amazon CloudWatch integrations. Automated deployment options have been improved and simplified using Kustomize scripts and Helm charts. Kubeflow on AWS 1.6.1 and PyTorch 1.12.1.

Metrics 72

Metrics Scripts Enterprise APIs 72

AWS Machine Learning

NOVEMBER 16, 2022

Upon a new model version registration, someone with the authority to approve the model based on the metrics should approve or reject the model. You can use Boto3 APIs as shown the following example, or you can use the AWS Management Console to create the model package. First we need to ensure the model package groups exists.

Accountability 88

Accountability Best practices Scripts Engineering 88

AWS Machine Learning

MAY 30, 2024

AWS Prototyping successfully delivered a scalable prototype, which solved CBRE’s business problem with a high accuracy rate (over 95%) and supported reuse of embeddings for similar NLQs, and an API gateway for integration into CBRE’s dashboards. The following diagram illustrates the web interface and API management layer.

Real estate 113

Real estate APIs Metrics Construction 113

AWS Machine Learning

NOVEMBER 9, 2022

The Triton server loads multiple models and exposes ports 8000, 8001, and 8002 as gRPC, HTTP, and metrics server. A complete API call from the client is as follows: The client assembles the request and initiates the request to a SageMaker endpoint. NVIDIA provides detailed documentation describing how to generate the TensorRT engine.

Engineering 85

Engineering Accountability APIs Metrics 85

AWS Machine Learning

SEPTEMBER 1, 2023

In this scenario, the generative AI application, designed by the consumer, must interact with the fine-tuner backend via APIs to deliver this functionality to the end-users. Models with larger context windows can understand and generate longer sequences of text, which can be useful for tasks involving longer conversations or documents.

Engineering 110

Engineering Accountability Construction APIs 110

AWS Machine Learning

SEPTEMBER 8, 2023

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

APIs 103

APIs Scripts Entertainment Personalization 103

AWS Machine Learning

JANUARY 26, 2024

Accelerate your security and AI/ML learning with best practices guidance, training, and certification AWS also curates recommendations from Best Practices for Security, Identity, & Compliance and AWS Security Documentation to help you identify ways to secure your training, development, testing, and operational environments.

Best practices 129

Best practices Government Engineering Accountability 129

AWS Machine Learning

FEBRUARY 19, 2024

An asynchronous API and Amazon OpenSearch Service connector make it easy to integrate the model into your neural search applications. Before you can write scripts that use the Amazon Bedrock API, you need to install the appropriate version of the AWS SDK in your environment. The vectors power speedy, accurate search experiences.

Scripts 106

Scripts APIs Entertainment Engineering 106

AWS Machine Learning

APRIL 23, 2024

Here are some features which we will cover: AWS CloudFormation support Private network policies for Amazon OpenSearch Serverless Multiple S3 buckets as data sources Service Quotas support Hybrid search, metadata filters, custom prompts for the RetreiveAndGenerate API, and maximum number of retrievals.

APIs 112

APIs Enterprise Scripts Accountability 112

AWS Machine Learning

APRIL 19, 2024

Solution overview In this section, we present a generic architecture that is similar to the one we use for our own workloads, which allows elastic deployment of models using efficient auto scaling based on custom metrics. The reverse proxy collects metrics about calls to the service and exposes them via a standard metrics API to Prometheus.

Metrics 107

Metrics APIs Scripts Construction 107

AWS Machine Learning

MAY 8, 2023

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM). Adds an IAM authorizer.

APIs 76

APIs Government Accountability Scripts 76

AWS Machine Learning

OCTOBER 11, 2022

It provides APIs powered by ML to extract key phrases, entities, sentiment analysis, and more. In Amazon Comprehend, you can classify your documents using two modes: multi-class or multi-label. Multi-class mode identifies one and only one class for each document, and multi-label mode identifies one or more labels for each document.

APIs 79

APIs Enterprise Engineering Accountability 79

AWS Machine Learning

APRIL 17, 2024

Metrics allow teams to understand workload behavior and optimize resource allocation and utilization, diagnose anomalies, and increase overall infrastructure efficiency. Metrics are exposed to Amazon Managed Service for Prometheus by the neuron-monitor DaemonSet, which deploys a minimal container, with the Neuron tools installed.

APIs 104

APIs Metrics Accountability Management 104

AWS Machine Learning

NOVEMBER 20, 2023

Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need to fine-tune it. When a user asks a question, it searches the vector database and retrieves documents that are most similar to the user’s query.

APIs 104

APIs Entertainment Accountability Customer Experience 104

AWS Machine Learning

JANUARY 19, 2024

Another example might be a healthcare provider who uses PLM inference endpoints for clinical document classification, named entity recognition from medical reports, medical chatbots, and patient risk stratification. The performance of the architecture is typically measured using metrics such as validation loss. training.py ).

Metrics 104

Metrics Scripts Benchmark Enterprise 104

AWS Machine Learning

DECEMBER 18, 2023

It is a document based storage that provides a fully managed database, with built-in full-text and vector Search , support for Geospatial queries, Charts and native support for efficient time series storage and querying capabilities. Solution overview Users persist their transactional time series data in MongoDB Atlas.

Finance 111

Finance APIs Analytics Scripts 111

AWS Machine Learning

SEPTEMBER 13, 2022

Amazon Comprehend is a fully managed and continuously trained natural language processing (NLP) service that can extract insight about content of a document or text. Often, the number of clusters in a corpus of documents is decided with the help of domain experts or by using some standard statistical analysis. Solution overview.

APIs 72

APIs Metrics Scripts Accountability 72

AWS Machine Learning

JANUARY 10, 2023

From there, we dive into how you can track and understand the metrics and performance of the SageMaker endpoint utilizing Amazon CloudWatch metrics. Metrics to track. Before we can get into load testing, it’s essential to understand what metrics to track to understand the performance breakdown of your SageMaker endpoint.

Best practices 78

Best practices Scripts APIs Metrics 78

AWS Machine Learning

JULY 21, 2022

As a result, this experimentation phase can produce multiple models, each created from their own inputs (datasets, training scripts, and hyperparameters) and producing their own outputs (model artifacts and evaluation metrics). We also illustrate how you can track your pipeline workflow and generate metrics and comparison charts.

Metrics 83

Metrics Scripts Enterprise Telecommunications 83

AWS Machine Learning

NOVEMBER 25, 2022

Defining the right objective metric matching your task. When our tuning job is complete, we look at some of the methods available to explore the results, both via the AWS Management Console and programmatically via the AWS SDKs and APIs. Collects metrics and logs. Amazon SageMaker Automatic Model Tuning. Runs the training.

Scripts 82

Scripts APIs Metrics Construction 82

AWS Machine Learning

MAY 8, 2023

To use TensorRT as a backend for Triton Inference Server, you need to create a TensorRT engine from your trained model using the TensorRT API. Inference requests arrive at the server via either HTTP/REST or by the C API , and are then routed to the appropriate per-model scheduler. script from the following cell.

Engineering 89

Engineering APIs Best practices Scripts 89

Babelforce

NOVEMBER 30, 2022

We’ve divided our definitions into the following categories: Metrics and measurables Technology Contact center terminology Business practices and methodology. Metrics and measurables. Active waiting calls metric. Application Programming Interface (API). An API is an application programming interface. Technology.

Contact Center 52

Contact Center Interactive Voice Response Call Center Automatic Callback 52

AWS Machine Learning

JUNE 6, 2023

Run your DLC container with a model training script to fine-tune the RoBERTa model. After model training is complete, package the saved model, inference scripts, and a few metadata files into a tar file that SageMaker inference can use and upload the model package to an Amazon Simple Storage Service (Amazon S3) bucket.

Scripts 75

Scripts APIs Benchmark Management 75

AWS Machine Learning

JULY 25, 2022

For detailed instructions on how to use the DGL-KE, refer to Training knowledge graph embeddings at scale with the Deep Graph Library and DGL-KE Documentation. For production, we wanted to invoke the model as a simple API call. With other standard metrics, the improvement ranged from 50–130%.

Scripts 75

Scripts Engineering Analytics APIs 75

AWS Machine Learning

MAY 9, 2023

Inference requests arrive at the server via either HTTP/REST or by the C API and are then routed to the appropriate per-model scheduler. SageMaker MMEs offer capabilities for running multiple deep learning or ML models on the GPU at the same time with Triton Inference Server, which has been extended to implement the MME API contract.

APIs 88

APIs Scripts Best practices Enterprise 88

AWS Machine Learning

MARCH 6, 2023

Best practices We discuss the following best practices in this post: Compute – SageMaker Training is a great API to launch CPU dataset preparation jobs and thousand-scale GPU jobs. The SageMaker jobs APIs, namely SageMaker Training and SageMaker Processing, excel for this type of tasks.

Best practices 85

Best practices APIs Transportation Scripts 85

AWS Machine Learning

APRIL 18, 2023

We make this possible in a few API calls in the JumpStart Industry SDK. Using the SageMaker API, we downloaded annual reports ( 10-K filings ; see How to Read a 10-K for more information) for a large number of companies. For further details regarding hyperparameters, refer to the official Hugging Face Trainer documentation.

Finance 71

Finance Scripts APIs Sales 71

AWS Machine Learning

SEPTEMBER 9, 2022

From its first implementation in automated document services, touchlessly processing millions of provider-patient documents, to its more recent work in virtual assistants and improving revenue cycle performance, athenahealth continues to apply AI to help drive efficiency, service capabilities, and better outcomes for providers and their patients.

Engineering 81

Engineering Healthcare APIs Scripts 81