AWS Machine Learning

OCTOBER 24, 2023

This post is co-authored by Dhurjati Brahma, Senior Systems Architect at T-Mobile US, Inc and Jim Chao, Principal Engineer/Architect at T-Mobile US, Inc and Nicholas Zellerhoff Associate Systems Architect at T-Mobile US, Inc. He holds a Master’s degree in Electrical Engineering from University of Alabama at Birmingham.

APIs 94

APIs Engineering Metrics Technology 94

Whitepages Pro

APRIL 24, 2019

Our latest product innovation, Transaction Risk API , was specifically built for easy integration into sophisticated machine learning (ML) models and is designed to help eCommerce merchants, marketplaces, payment processors, and others manage payment fraud. Transaction Risk API delivers a response within 100 ms to meet this need.

APIs 40

APIs Marketing Engineering Metrics 40

AWS Machine Learning

OCTOBER 18, 2023

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Purina’s solution is deployed as an API Gateway HTTP endpoint, which routes the requests to obtain pet attributes.

APIs 99

APIs Metrics Consulting Consulting 99

AWS Machine Learning

JANUARY 12, 2023

This is guest post by Andy Whittle, Principal Platform Engineer – Application & Reliability Frameworks at The Very Group. The overriding goal for The Very Group’s engineering team was to prevent any PII data from reaching documents within Elasticsearch. Overview of solution. Some decisions had to be made to enable the solution.

Engineering 111

Engineering APIs Accountability Metrics 111

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.

APIs 94

APIs Accountability Metrics Engineering 94

AWS Machine Learning

FEBRUARY 7, 2024

Deploy the API to make predictions. Review the Model performance overall score and all other metrics that Amazon Fraud Detector generated for this model. The following diagram represents each stage in a mortgage document fraud detection pipeline. Select your options and train the model. Create the model. Review model performance.

APIs 112

APIs Accountability Metrics Engineering 112

AWS Machine Learning

APRIL 19, 2023

They use the DJL PyTorch engine to initialize the model predictor. The DJL continues to grow in its ability to support different hardware, models, and engines. The architecture of DJL is engine agnostic. When the DJL loads, it finds all the engine implementations available in the class path using Java’s ServiceLoader.

Engineering 78

Engineering APIs Scripts Education 78

AWS Machine Learning

NOVEMBER 22, 2023

You can save time, money, and labor by implementing classifications in your workflow, and documents go to downstream applications and APIs based on document type. This helps you avoid throttling limits on API calls due to polling the Get* APIs. The metrics should include business metrics and technical metrics.

APIs 97

APIs Metrics Enterprise Benchmark 97

AWS Machine Learning

SEPTEMBER 9, 2022

The platform has shown a 3% boost to customer engagement metrics tracked (liking a show, following a creator, enabling upcoming show notifications) since its launch in May 2022. The independent nature of each individual metric transformation also makes Lambda, which is a stateless service on its own, a good fit for this problem.

Personalization 75

Personalization APIs Engineering Metrics 75

AWS Machine Learning

APRIL 17, 2023

You can use Amazon Fraud Detector to build customized fraud detection models using your own historical dataset, add decision logic using the built-in rules engine, and orchestrate risk decision workflows with a click of a button. The following table defines these metrics. AUC uncertainty interval > 0.3

APIs 75

APIs Government Metrics Engineering 75

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 80

Scripts APIs Metrics Engineering 80

AWS Machine Learning

NOVEMBER 21, 2023

After checking the accuracy metrics for the locally-trained model, we can move the training into Amazon SageMaker. It can also be used as a standard REST API if deployed together with an AWS Lambda function and API gateway, which can be integrated with any web applications.

Engineering 91

Engineering APIs Scripts Automotive 91

AWS Machine Learning

MARCH 27, 2024

That’s why it’s good practice to check if you actually need to fine-tune your model for your use case or if prompt engineering is sufficient. With some prompt engineering, we can provide more details to get closer to the look of our favorite pets. The data remains in the same Region where the API call is processed.

APIs 90

APIs Accountability Engineering Entertainment 90

AWS Machine Learning

DECEMBER 1, 2022

You can then compare the performance of the two versions using metrics such as latency and error rate. Optionally, you can monitor the variants through a built-in dashboard with a side-by-side comparison of the performance metrics. Please refer to the CreateModel API here. Pre-requisites. Step 1 – Create a shadow test.

APIs 81

APIs Metrics Management Engineering 81

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 76

Scripts Engineering APIs Big data 76

AWS Machine Learning

NOVEMBER 8, 2023

We have developed a MONAI Deploy connector to AHI to integrate medical imaging AI applications with subsecond image retrieval latencies at scale powered by cloud-native APIs. AHI provides API access to ImageSet metadata and ImageFrames. Metadata contains all DICOM attributes in a JSON document.

Healthcare 99

Healthcare APIs Enterprise Engineering 99

Nicereply

JANUARY 30, 2023

This can include anything from knowing how many people you need to hire and knowing exactly what metrics you need to hit, to determining if there are new tools that you’ll need to use in order to a ccomplish your goals. If so, what are some levers you might be able to pull to shift that metric, too?

Metrics 98

Metrics Finance APIs Customer Support 98

AWS Machine Learning

MARCH 28, 2024

You can scrape the filings from EDGAR directly, or use APIs in Amazon SageMaker with a few lines of code, for any period of time and for a large number of tickers (i.e., For the latter, the authors assign sampling weights for each data points according the metric values, and then randomly sample k data points to meet the training budget.

Finance 101

Finance Metrics Banking Engineering 101

AWS Machine Learning

MARCH 13, 2023

This post is co-written with Mahima Agarwal, Machine Learning Engineer, and Deepak Mettem, Senior Engineering Manager, at VMware Carbon Black VMware Carbon Black is a renowned security solution offering protection against the full spectrum of modern cyberattacks.

Engineering 85

Engineering APIs Metrics Management 85

AWS Machine Learning

AUGUST 30, 2023

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. This metric compares an automatically produced summary against a reference or a set of references (human-produced) summary or translation.

Healthcare 116

Healthcare APIs Scripts Metrics 116

AWS Machine Learning

OCTOBER 5, 2022

Each year, bad actors compromise billions of accounts through stolen credentials, phishing, social engineering, and multiple forms of ATO. For a real-time prediction, you call the GetEventPrediction API after a user presents valid login credentials to quantify the risk of ATO. billion in 2021 compared with 2020. Upload event data.

Accountability 73

Accountability APIs Metrics Engineering 73

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 107

Engineering Accountability Construction APIs 107

AWS Machine Learning

SEPTEMBER 9, 2022

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. This post is the first in a two-part series.

Analytics 72

Analytics Engineering APIs Metrics 72

AWS Machine Learning

APRIL 24, 2023

In this post, we explore how AWS customer Pro360 used the Amazon Comprehend custom classification API , which enables you to easily build custom text classification models using your business-specific labels without requiring you to learn machine learning (ML), to improve customer experience and reduce operational costs.

APIs 64

APIs Customer Experience Feedback Chatbots 64

AWS Machine Learning

JULY 24, 2023

This blog post was co-authored, and includes an introduction, by Zilong Bai, senior natural language processing engineer at Patsnap. Because there is no such existing feature in a patent search engine (to their best knowledge), Patsnap believes adding this feature will increase end-user stickiness. gpt2 and predictor.py client('sts').get_caller_identity()['Account']

APIs 69

APIs Engineering Construction Benchmark 69

AWS Machine Learning

JULY 7, 2022

You can use APIs or AWS CloudFormation (see Creating Amazon Lex V2 resources with AWS CloudFormation ) to manage the bot programmatically. Identify user experience metrics – Defining the conversational experience can be hard. You should evaluate the user experience, and invest in an automated testing to generate key metrics.

Best practices 78

Best practices Metrics APIs Accountability 78

AWS Machine Learning

NOVEMBER 16, 2023

With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production. Another important metric is the efficiency for data science users.

Healthcare 93

Healthcare Government Engineering APIs 93

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. Added integration with Amazon Managed Service for Prometheus (AMP) and Amazon Managed Grafana to monitor metrics with Kubeflow on AWS. and PyTorch 1.12.1.

Metrics 70

Metrics Scripts Enterprise APIs 70

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. A TrainingStep to train the model using the training, validation, and test datasets and export the mean Average Precision (mAP) metric for the model.

Scripts 97

Scripts Construction Engineering APIs 97

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 126

Best practices Government Engineering Accountability 126

AWS Machine Learning

FEBRUARY 15, 2024

Engineers look for abnormal data when investigating root causes for a fault or as warning indicators for future faults, and performance managers examine abnormal data to identify potential improvements. The predicted value indicates the expected value for our target metric based on the training data.

Metrics 96

Metrics Analytics APIs Big data 96

Whitepages Pro

MARCH 1, 2019

For a company that provides API products, a key metric on the performance of an API is to track and iterate on its response time. We care about this metric because customers have different response time needs based on their workflows and business problems. What is response time? Why do response times matter?

APIs 40

APIs Engineering Metrics Marketing 40

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. Based on these metrics an informed decision can be made. Neuron compilation explained The Neuron SDK’s API closely resembles the PyTorch Python API. 3 Inf1.24xlarge 16 64 1.5 code as the entry point.

Scripts 76

Scripts APIs Engineering Best practices 76

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. Prepare models and build the engine. Test the TensorRT engine.

Engineering 82

Engineering Accountability APIs Metrics 82

AWS Machine Learning

JUNE 24, 2022

In a previous post , we talked about analyzing and tagging assets stored in Veeva Vault PromoMats using Amazon AI services and the Veeva Vault Platform’s APIs. Anomaly detection – You can share Veeva PromoMats documents to Amazon Lookout for Metrics for anomaly detection.

APIs 75

APIs Healthcare SaaS Engineering 75

AWS Machine Learning

JUNE 5, 2023

Desired target metrics, improvement monitoring, and convergence detection monitors the performance of the model and assists with early stopping if the models don’t improve after a defined number of training jobs. Iaroslav Shcherbatyi is a Machine Learning Engineer at AWS.

APIs 80

APIs Enterprise Benchmark Metrics 80

AWS Machine Learning

MARCH 13, 2023

Finally, we use Amazon API Gateway as a way of integrating with our front end, the Ground Truth labeling application, to provide secure authentication to our backend. In the following figure, we show the ModelLatency metric natively emitted by SageMaker real-time inference endpoints.

Metrics 71

Metrics APIs Feedback Engineering 71