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 63

APIs Customer Experience Feedback Chatbots 63

AWS Machine Learning

NOVEMBER 3, 2022

Before you get started, refer to Part 1 for a high-level overview of the insurance use case with IDP and details about the data capture and classification stages. In Part 1, we saw how to use Amazon Textract APIs to extract information like forms and tables from documents, and how to analyze invoices and identity documents.

Analytics 77

Analytics APIs Healthcare Big data 77

AWS Machine Learning

DECEMBER 21, 2022

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Table formats provide a way to abstract data files as a table. You can also use the FeatureGroup().put_record

Scripts 75

Scripts Engineering APIs Big data 75

AWS Machine Learning

OCTOBER 27, 2022

We can then call a Forecast API to create a dataset group and import data from the processed S3 bucket. We use the AutoPredictor API, which is also accessible through the Forecast console. When those datasets are ready, we can start to train the predictor. Ray Wang is a Solutions Architect at AWS.

APIs 97

APIs Best practices Metrics Government 97

AWS Machine Learning

NOVEMBER 27, 2023

However, these models require massive amounts of clean, structured training data to reach their full potential. Most real-world data exists in unstructured formats like PDFs, which requires preprocessing before it can be used effectively. According to IDC , unstructured data accounts for over 80% of all business data today.

Engineering 76

Engineering APIs Big data Accountability 76

AWS Machine Learning

AUGUST 15, 2022

More specifically, we need to identify the customer’s savings and checking account numbers in the bank statement. The entities in this file are going to be specific to our business needs (savings and checking account numbers). Document is a wrapper function used to help parse the JSON response from the API. TDocumentSchema().load(response)

Banking 76

Banking APIs Accountability Analytics 76

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 98

Scripts APIs Government Analytics 98

AWS Machine Learning

JULY 24, 2023

They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. In this section, we show how to build your own container, deploy your own GPT-2 model, and test with the SageMaker endpoint API. implement the model and the inference API. gpt2 and predictor.py

APIs 68

APIs Engineering Construction Benchmark 68

AWS Machine Learning

JANUARY 26, 2024

In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

Best practices 125

Best practices Government Engineering Accountability 125

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. Aamna Najmi is a Data Scientist with AWS Professional Services.

APIs 64

APIs Scripts Engineering Technical Support 64

Hodusoft

AUGUST 30, 2022

Businesses of every size, type, and industry can benefit from using cloud services for a variety of reasons such as: Data backup Software development and testing Email Disaster recovery Virtual desktops Big data analytics Customer-facing web applications, and more. The most popular cloud-based services: UCaaS, CCaas, and CPaaS.

APIs 52

APIs Interactive Voice Response Contact Center voip 52

AWS Machine Learning

AUGUST 2, 2023

We demonstrate CDE using simple examples and provide a step-by-step guide for you to experience CDE in an Amazon Kendra index in your own AWS account. After ingestion, images can be searched via the Amazon Kendra search console, API, or SDK. About the Authors Charalampos Grouzakis is a Data Scientist within AWS Professional Services.

Enterprise 73

Enterprise Healthcare APIs Big data 73

AWS Machine Learning

JULY 19, 2022

We set the OutputFormat to mp3 , which tells Amazon Polly to generate an audio stream for this API call. We again use the start_speech_synthesis_task method but specify OutputFormat to json , which tells Amazon Polly to generate speech marks for this API call. Prerequisites. AWS Cloud Development Kit (AWS CDK). Deploy the solution.

Engineering 86

Engineering APIs Education Best practices 86

Talkdesk

JANUARY 16, 2018

With technological advancements in speech recognition, artificial intelligence and big data, the spoken words in those calls can now be used to elicit actionable insights from spoken information. Using recorded call data to construct predictive models provides the means for automating call disposition.

Analytics 40

Analytics Call Center Customer centricity Construction 40

Talkdesk

JANUARY 16, 2018

With technological advancements in speech recognition, artificial intelligence and big data, the spoken words in those calls can now be used to elicit actionable insights from spoken information. Using recorded call data to construct predictive models provides the means for automating call disposition.

Analytics 40

Analytics Call Center Customer centricity Construction 40

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).

APIs 72

APIs Government Accountability Scripts 72

AWS Machine Learning

MAY 3, 2023

Furthermore, SageMaker Processing provides an API interface for running, monitoring, and evaluating the workload. Workflows would fail if the client data volume increased, or the cost would be unjustifiable if the data volume decreased in production. Sharmo Sarkar is a Senior Manager at Vericast.

Engineering 72

Engineering Metrics APIs Big data 72

AWS Machine Learning

OCTOBER 4, 2022

One of the main drivers for new innovations and applications in ML is the availability and amount of data along with cheaper compute options. To follow along in this post, you need the following: An AWS account. Register model step (model package). Fail step (run failed). The following diagram illustrates our pipeline. Prerequisites.

Scripts 74

Scripts Engineering Management APIs 74

AWS Machine Learning

MARCH 22, 2023

An AWS account with permissions to create AWS Identity and Access Management (IAM) policies and roles. Access and permissions to configure IDP to register Data Wrangler application and set up the authorization server or API. For data scientist: An S3 bucket that Data Wrangler can use to output transformed data.

APIs 82

APIs Engineering Analytics Scripts 82

AWS Machine Learning

FEBRUARY 1, 2024

Ingesting from these sources is different from the typical data sources like log data in an Amazon Simple Storage Service (Amazon S3) bucket or structured data from a relational database. In the low-latency case, you need to account for the time it takes to generate the embedding vectors.

Best practices 116

Best practices Engineering SaaS APIs 116

Enghouse Interactive

JULY 10, 2018

Making significant changes to an account. For Partner Colorado, Enghouse’s use of open APIs allows integration with the in-house CRM. Instead of having to toggle back and forth between different screens and applications, agents proactively receive relevant and useful data on callers via ScreenPop.

Self service 40

Self service CRM Contact Center Analytics 40

AWS Machine Learning

JUNE 19, 2023

For provisioning Studio in your AWS account and Region, you first need to create an Amazon SageMaker domain—a construct that encapsulates your ML environment. When the AD user is assigned to an AD group, an IAM Identity Center API ( CreateGroupMembership ) is invoked, and SSO group membership is created.

APIs 72

APIs Accountability Construction Enterprise 72

AWS Machine Learning

AUGUST 31, 2023

As you scale your models, projects, and teams, as a best practice we recommend that you adopt a multi-account strategy that provides project and team isolation for ML model development and deployment. Depending on your governance requirements, Data Science & Dev accounts can be merged into a single AWS account.

Government 94

Government Accountability Enterprise Engineering 94

AWS Machine Learning

AUGUST 29, 2023

This architecture design represents a multi-account strategy where ML models are built, trained, and registered in a central model registry within a data science development account (which has more controls than a typical application development account).

Scripts 75

Scripts APIs Enterprise Accountability 75

AWS Machine Learning

JULY 29, 2022

It’s aligned with the AWS recommended practice of using temporary credentials to access AWS accounts. At the time of this writing, you can create only one domain per AWS account per Region. To implement the strong separation, you can use multiple AWS accounts with one domain per account as a workaround.

Management 75

Management APIs Accountability Construction 75

AWS Machine Learning

JUNE 24, 2022

After the data scientists have proven that ML can solve the business problem and are familiarized with SageMaker experimentation, training, and deployment of models, the next step is to start productionizing the ML solution. In the same account, Amazon SageMaker Feature Store can be hosted, but we don’t cover it this post.

Enterprise 93

Enterprise Engineering Accountability APIs 93

AWS Machine Learning

AUGUST 26, 2022

We explore two ways of obtaining the same result: via JumpStart’s graphical interface on Amazon SageMaker Studio , and programmatically through JumpStart APIs. The following sections provide a step-by-step demo to perform semantic segmentation with JumpStart, both via the Studio UI and via JumpStart APIs. Solution overview.

APIs 80

APIs Scripts Enterprise Big data 80

AWS Machine Learning

SEPTEMBER 6, 2023

Prerequisites To try out the Amazon Kendra connector for AEM using this post as a reference, you need the following: An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. To check, view the data sources and verify if the last sync was successful. Choose Save or Add Secret.

Management 100

Management Enterprise Analytics Finance 100

AWS Machine Learning

AUGUST 31, 2023

As you scale your models, projects, and teams, as a best practice we recommend that you adopt a multi-account strategy that provides project and team isolation for ML model development and deployment. Depending on your governance requirements, Data Science & Dev accounts can be merged into a single AWS account.

Government 52

Government Accountability Enterprise Engineering 52

Natalie Petouhof

MAY 25, 2016

Market-leading and early adopter organizations must account for how IoT initiatives deliver a customer- centric experience.

Customer centricity 45

Customer centricity Technology Customer Experience Big data 45

AWS Machine Learning

DECEMBER 1, 2022

The Model dashboard is a centralized repository of all models that have been created in the account. Organizations can dive deep to identify which models have missing or inactive monitors and add them using SageMaker APIs to ensure all models are being checked for data drift, model drift, bias drift, and feature attribution drift.

Government 80

Government Metrics APIs Engineering 80

AWS Machine Learning

APRIL 19, 2023

This example notebook demonstrates the pattern of using Feature Store as a central repository from which data scientists can extract training datasets. In addition to creating a training dataset, we use the PutRecord API to put the 1-week feature aggregations into the online feature store nightly. Nov-01,22:01:00 1 74.99 …9843 99.50

Engineering 79

Engineering Analytics APIs Enterprise 79

aircall

APRIL 16, 2021

SaaS works well for a variety of general use cases, including: Data backup. Big data analytics. Flexibility – SaaS uses an open API (application programming interface) technology. Use SaaS software to ensure accountability for each support agent. It doesn’t discriminate! Email platforms. Disaster recovery.

SaaS 62

SaaS Sales Coaching APIs 62

AWS Machine Learning

DECEMBER 1, 2022

They have a wide variety of personas to account for, each with their own unique sets of needs, and building the right sets of permissions policies to meet those needs can sometimes be an inhibitor to agility. Sometimes administrators give access to the console for ML practitioners to debug issues with their Studio environment. Conclusion.

Management 75

Management Government Enterprise APIs 75

AWS Machine Learning

SEPTEMBER 9, 2022

Access to AWS services from Katib and from pipeline pods using the AWS IAM Roles for Service Accounts (IRSA) integration with Kubeflow Profiles. Prior to our adoption of Kubeflow on AWS, our data scientists used a standardized set of tools and a process that allowed flexibility in the technology and workflow used to train a given model.

Engineering 77

Engineering Healthcare APIs Scripts 77

Interactions

SEPTEMBER 19, 2019

In 2013, Aloha (NCR) and MICROS (Oracle) accounted for about 43% of the restaurant POS market; by 2017, that number was down to about 30% and continues to fall. A big point of discussion during breakout sessions and over drinks (yes, really!) was the concept of standardized APIs across multiple technologies.

APIs 70

APIs Big data Engineering Sales 70

AWS Machine Learning

JULY 21, 2022

Compare and evaluate experiments – The integration of Experiments with Amazon SageMaker Studio makes it easy to produce data visualizations and compare different trials. You can also access the trial data via the Python SDK to generate your own visualization using your preferred plotting libraries. Suggested readings.

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Metrics Scripts Enterprise Telecommunications 80