AWS Machine Learning

APRIL 24, 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 using a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

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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.

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AWS Machine Learning

JANUARY 10, 2024

The solution uses AWS Lambda , Amazon API Gateway , Amazon EventBridge , and SageMaker to automate the workflow with human approval intervention in the middle. The approver approves the model by following the link in the email to an API Gateway endpoint. API Gateway invokes a Lambda function to initiate model updates.

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AWS Machine Learning

MAY 16, 2024

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. Real-time recommendation inference The inference phase consists of the following steps: The client application makes an inference request to the API gateway.

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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. This solution deploys an Amazon EKS cluster with a node group that includes Inf1 instances. or later NPM version 10.0.0

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AWS Machine Learning

AUGUST 26, 2024

The GenASL web app invokes the backend services by sending the S3 object key in the payload to an API hosted on Amazon API Gateway. API Gateway instantiates an AWS Step Functions The state machine orchestrates the AI/ML services Amazon Transcribe and Amazon Bedrock and the NoSQL data store Amazon DynamoDB using AWS Lambda functions.

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AWS Machine Learning

NOVEMBER 15, 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, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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AWS Machine Learning

NOVEMBER 26, 2024

The Sophos Artificial Intelligence (AI) group (SophosAI) oversees the development and maintenance of Sophos’s major ML security technology. To gain a general understanding of the quality of a model’s incident summarization, we use a set of five distinct metrics and rely on a dataset comprising of N incidents.

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AWS Machine Learning

JUNE 5, 2024

In an Email phishing attempt, an email is sent as a mode of communication to group of people. You can train a custom classifier using either the Amazon Comprehend console or API. This confusion matrix provides metrics on how well the model performed in training.

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AWS Machine Learning

NOVEMBER 1, 2024

Users can manage and use application inference profiles using Bedrock APIs or the boto3 SDK: CreateInferenceProfile : Initiates a new inference profile, allowing users to configure the parameters for the profile. ConverseStream API : Similar to the Converse API but supports streaming responses for real-time interactions.

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AWS Machine Learning

NOVEMBER 21, 2023

Layout extends Amazon Textract’s word and line detection by automatically grouping the text into these layout elements and sequencing them according to human reading patterns. The LAYOUT feature of AnalyzeDocument API can now detect up to ten different layout elements in a document’s page. Returned as LAYOUT_SECTION_HEADER block type.

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AWS Machine Learning

JULY 25, 2024

This solution is applicable if you’re using managed nodes or self-managed node groups (which use Amazon EC2 Auto Scaling groups ) on Amazon EKS. The node recovery agent is a separate component that periodically checks the Prometheus metrics exposed by the node problem detector. and public.ecr.aws. and public.ecr.aws.

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AWS Machine Learning

OCTOBER 2, 2024

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the user’s request. In Part 1, we focus on creating accurate and reliable agents.

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ProProfs Blog

JUNE 26, 2020

Application Program Interface (API). Application Programming Interface (API) is a combination of various protocols, tools, and codes. The function of the API enables apps to communicate with each other. Chat Response Time is a metric to monitor how much time your operators took to respond to chats. Chat Duration.

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AWS Machine Learning

JULY 30, 2024

The response from API calls are displayed to the end-user. Add a user to the Amazon Q Business application To start using the Amazon Q Business application, you can add users or groups to the Amazon Q Business application from your IAM Identity Center instance. Choose Add groups and users. Choose Add existing users and groups.

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AWS Machine Learning

OCTOBER 16, 2023

Apart from GPU provisioning, this setup also required data scientists to build a REST API wrapper for each model, which was needed to provide a generic interface for other company services to consume, and to encapsulate preprocessing and postprocessing of model data. Two MMEs were created at Veriff, one for staging and one for production.

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AWS Machine Learning

SEPTEMBER 28, 2023

A Generative AI Gateway can help large enterprises control, standardize, and govern FM consumption from services such as Amazon Bedrock , Amazon SageMaker JumpStart , third-party model providers (such as Anthropic and their APIs), and other model providers outside of the AWS ecosystem. What is a Generative AI Gateway?

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AWS Machine Learning

JANUARY 5, 2024

Query training results: This step calls the Lambda function to fetch the metrics of the completed training job from the earlier model training step. RMSE threshold: This step verifies the trained model metric (RMSE) against a defined threshold to decide whether to proceed towards endpoint deployment or reject this model.

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AWS Machine Learning

MAY 4, 2023

Time series forecasting using Forecast The workflow for Forecast involves the following common concepts: Importing datasets – In Forecast, a dataset group is a collection of datasets, schema, and forecast results that go together. For more details, refer to Importing Datasets. For more information, refer to Training Predictors.

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AWS Machine Learning

JUNE 20, 2024

The idea is to use metrics to compare experiments during development. Running predictions on the test set records results with the metrics needed to compare experiments. A common metric is the accuracy, which is the percentage of the correct results. For example, it can be used for API access, building JSON data, and more.

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AWS Machine Learning

DECEMBER 9, 2024

However, keeping track of numerous experiments, their parameters, metrics, and results can be difficult, especially when working on complex projects simultaneously. We define the SageMaker-associated private subnets and security group in the configuration file. We specify the security group and subnets information in VpcConfig.

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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.

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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.

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AWS Machine Learning

NOVEMBER 14, 2023

During fine-tuning, we integrate SageMaker Experiments Plus with the Transformers API to automatically log metrics like gradient, loss, etc. HuggingFace Transformer APIs allow users to track metrics during training tasks through Callbacks. QLoRA reduces the computational cost of fine-tuning by quantizing model weights.

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AWS Machine Learning

AUGUST 3, 2022

With Feature Store, you have always been able to add metadata at the feature group level. For example, the information can include a description of the feature, the date it was last modified, its original data source, certain metrics, or the level of sensitivity. The following figure shows example feature groups and feature metadata.

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AWS Machine Learning

JUNE 27, 2023

This step produces an expanded report containing the model’s metrics. The AI/ML architecture for EarthSnap is designed around a series of AWS services: Sagemaker Pipeline runs using one of the methods mentioned above (CodeBuild, API, manual) that trains the model and produces artifacts and metrics.

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AWS Machine Learning

JUNE 25, 2024

A new automatic dashboard for Amazon Bedrock was added to provide insights into key metrics for Amazon Bedrock models. From here you can gain centralized visibility and insights to key metrics such as latency and invocation metrics. Optionally, you can select a specific model to isolate the metrics to one model.

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AWS Machine Learning

MAY 31, 2023

Triton with PyTorch backend The PyTorch backend is designed to run TorchScript models using the PyTorch C++ API. When configuring your auto scaling groups for SageMaker endpoints, you may want to consider SageMakerVariantInvocationsPerInstance as the primary criteria to determine the scaling characteristics of your auto scaling group.

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AWS Machine Learning

FEBRUARY 14, 2023

After specifying the metrics that you want to track, you can identify which campaigns and recommenders are most impactful and understand the impact of recommendations on your business metrics. All customers want to track the metric that is most important for their business.

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AWS Machine Learning

NOVEMBER 17, 2022

Their production segment is therefore an integral building block for delivering on their mission—with a clearly stated ambition to become world-leading on metrics such as safety, environmental footprint, quality, and production costs. Yara has built APIs using Amazon API Gateway to expose the sensor data to applications such as ELC.

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AWS Machine Learning

NOVEMBER 13, 2024

Because SageMaker Model Cards and SageMaker Model Registry were built on separate APIs, it was challenging to associate the model information and gain a comprehensive view of the model development lifecycle. SageMaker Model Registry catalogs your models along with their versions and associated metadata and metrics for training and evaluation.

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AWS Machine Learning

NOVEMBER 22, 2023

Define goals and metrics – The function needs to deliver value to the organization in different ways. Establish regular cadence – The group should come together regularly to review their goals and metrics. Establish regular cadence – The group should come together regularly to review their goals and metrics.

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AWS Machine Learning

APRIL 4, 2024

A Lambda function performs the same data transformation operations as the batch ingestion job at the individual record level, and ingests the data into Amazon Personalize using the PutEvents and PutItems APIs. For more information about these metrics, see Evaluating a solution version with metrics.

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AWS Machine Learning

NOVEMBER 22, 2023

All of the AWS AI services (for example, Amazon Textract , Amazon Comprehend , or Amazon Comprehend Medical ) used in IDP solutions are fully managed AI services where AWS secures their physical infrastructure, API endpoints, OS, and application code, and handles service resilience and failover within a given region.

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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.

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Inbenta

JULY 3, 2020

This way, you can easily search through your contacts and keep them grouped and organized. Statistics – WhatsApp for Business lets you access key metrics like how many of your messages were sent, delivered, and read. WhatsApp Business offers an API (Application Programming Interface). WhatsApp Business chatbots.

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AWS Machine Learning

SEPTEMBER 18, 2023

Ingesting features into the feature store contains the following steps: Define a feature group and create the feature group in the feature store. Ingest the prepared data into the feature group by using the Boto3 SDK. Prepare the source data for the feature store by adding an event time and record ID for each row of data.

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