AWS Machine Learning

MARCH 23, 2023

Leidos is a FORTUNE 500 science and technology solutions leader working to address some of the world’s toughest challenges in the defense, intelligence, homeland security, civil, and healthcare markets. In this post, we show how to activate privacy-preserving ML predictions for the most highly regulated environments. resource("s3").Bucket

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AWS Machine Learning

DECEMBER 21, 2022

By the end of this post, you will know how to create feature groups using the Iceberg format, execute Iceberg’s table management procedures using Amazon Athena , and schedule these tasks to run autonomously. If you are a Spark user, you will also learn how to execute the same procedures using Spark. You can also use the FeatureGroup().put_record

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AWS Machine Learning

DECEMBER 19, 2022

This blog post demonstrates how to perform ML inference using an object detection model from the PyTorch Model Zoo within SageMaker. Finally, we will deploy the ML model, perform inference on it using SageMaker Batch Transform, and inspect the ML model output and learn how to interpret the results. Step 1: Setup. Architecture diagram.

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AWS Machine Learning

NOVEMBER 1, 2022

In this post, we show how to create an end-to-end ML workflow to train and evaluate an Autopilot generated ML model using Pipelines and register it in the SageMaker model registry. We use a Lambda step because the API call to Autopilot is lightweight. script creates an Autopilot job. SageMaker pipeline steps.

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AWS Machine Learning

NOVEMBER 21, 2022

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. Healthcare and life sciences. Fraud detection.

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AWS Machine Learning

FEBRUARY 13, 2023

With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to marketing), the primary focus shifts to efficiency when building and training models at scale. The steps are as follows: Open AWS Cloud9 on the console.

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AWS Machine Learning

AUGUST 3, 2023

In the current scenario, you need to dedicate resources to accomplish such tasks using human review and complex scripts. Amazon Bedrock is a fully managed service that makes FMs from leading AI startups and Amazon available through an API, so you can find the model that best suits your requirements.

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AWS Machine Learning

JULY 11, 2023

However, organizations operating in regulated industries like banking, insurance, and healthcare operate in environments that have strict data privacy and networking controls in place. To achieve this, we set up a configuration file, develop the training script, and run the training code. and model.py gamma: float = 0.7,

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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). The first allows you to run a Python script from any server or instance including a Jupyter notebook; this is the quickest way to get started.

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AWS Machine Learning

JANUARY 26, 2024

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. We first delve into the vulnerabilities, threats, and risks that arise from the implementation, deployment, and use of LLM solutions, and provide guidance on how to start innovating with security in mind.

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AWS Machine Learning

SEPTEMBER 14, 2023

Please read this post to learn how to implement the RAG approach with Amazon Kendra. Amazon API Gateway hosts a REST API with various endpoints to handle user requests that are authenticated using Amazon Cognito. For this scenario, an employee has a question in how to proceed and edit an internal issue ticketing ticket.

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AWS Machine Learning

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. In this post, we discuss how to operationalize generative AI applications using MLOps principles leading to foundation model operations (FMOps). 15K available FM reference Step 1.

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AWS Machine Learning

JANUARY 25, 2023

In this post, we provide an overview of how to deploy and run inference with the Stable Diffusion upscaler model in two ways: via JumpStart’s user interface (UI) in Amazon SageMaker Studio , and programmatically through JumpStart APIs available in the SageMaker Python SDK.

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AWS Machine Learning

APRIL 10, 2023

In this post, we present a comprehensive guide on deploying and running inference using the Stable Diffusion inpainting model in two methods: through JumpStart’s user interface (UI) in Amazon SageMaker Studio , and programmatically through JumpStart APIs available in the SageMaker Python SDK.

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AWS Machine Learning

AUGUST 17, 2023

Option B: Use a SageMaker Processing job with Spark In this option, we use a SageMaker Processing job with a Spark script to load the original dataset from Amazon Redshift, perform feature engineering, and ingest the data into SageMaker Feature Store. The environment preparation process may take some time to complete.

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AWS Machine Learning

DECEMBER 5, 2023

The solution discussed in this post can easily be applied to other businesses/use-cases as well, such as healthcare, manufacturing, and research. Amazon Comprehend custom classification API is used to organize your documents into categories (classes) that you define. The following diagram outlines the proposed solution architecture.

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AWS Machine Learning

FEBRUARY 20, 2023

In this post, we provide an overview of how to fine-tune the Stable Diffusion model in two ways: programmatically through JumpStart APIs available in the SageMaker Python SDK , and JumpStart’s user interface (UI) in Amazon SageMaker Studio. Fine-tuning large models like Stable Diffusion usually requires you to provide training scripts.

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AWS Machine Learning

MARCH 14, 2024

With the rapid advancement of FMs, it’s an exciting time to harness their power, but also crucial to understand how to properly use them to achieve business outcomes. Frameworks like LangChain and certain FMs such as Claude models provide function-calling capabilities to interact with APIs and tools.

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AWS Machine Learning

JANUARY 19, 2024

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model performance and reduce inference times. Then the payload is passed to the SageMaker endpoint invoke API via the BotoClient to simulate real user requests. training.py ).

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AWS Machine Learning

MAY 3, 2023

In this post, we demonstrate how to implement a RAG workflow by combining the capabilities of Amazon Kendra with LLMs to create state-of-the-art GenAI applications providing conversational experiences over your enterprise content. Follow the instructions in the GitHub repo to install the KendraIndexRetriever interface and sample applications.

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AWS Machine Learning

NOVEMBER 1, 2022

For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. The Step Functions state machine, S3 bucket, Amazon API Gateway resources, and Lambda function codes are stored in the GitHub repo. The following figure illustrates our Step Function workflow.

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JivoChat

APRIL 23, 2023

Basically, a chatbot will: Use a data center to understand how to build the responses; Give answers that are as close as possible as a human would do by using NLP; Learn how to improve its interaction through machine learning; Collect key information; Generate automated responses to user inquiries.

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AWS Machine Learning

SEPTEMBER 9, 2022

Example components of the standardized tooling include a data ingestion API, security scanning tools, the CI/CD pipeline built and maintained by another team within athenahealth, and a common serving platform built and maintained by the MLOps team. Tyler Kalbach is a Principal Member of Technical Staff at athenahealth.

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NobelBiz

JUNE 26, 2023

Learn more about the best practices in contact center staffing, how to increase agent satisfaction & retention, and many more call center human resources tips and tricks. Learn more about how to optimize your dialing operations. Learn more about how to upgrade your business phone system.

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AWS Machine Learning

JUNE 28, 2022

Time series forecasting is useful in multiple fields, including retail, finance, logistics, and healthcare. In this post, we show you how to deploy a demand forecasting solution using Amazon SageMaker JumpStart. Time series forecasting is a technique that predicts future time series data based on historical data. Launch the solution.

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AWS Machine Learning

NOVEMBER 1, 2023

The TGI framework underpins the model inference layer, providing RESTful APIs for robust integration and effortless accessibility. Supplementing our auditory data processing, the Whisper ASR is also furnished with a RESTful API, enabling streamlined voice-to-text conversions.

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AWS Machine Learning

SEPTEMBER 7, 2023

This post details how to set up container-based GPU metrics and provides an example of collecting these metrics from EKS pods. The EKS API metadata has been combined with the DCGM metrics data, resulting in the provided pod-based GPU metrics. eks-create.sh eksctl create cluster -f /eks/conf/eksctl/yaml/eks-gpu-g5.yaml eks-0a21954 m5.xlarge

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