AWS Machine Learning

MARCH 23, 2023

The predictions (inference) use encrypted data and the results are only decrypted by the end consumer (client side). To demonstrate this, we show an example of customizing an Amazon SageMaker Scikit-learn, open sourced, deep learning container to enable a deployed endpoint to accept client-side encrypted inference requests.

Scripts 93

Scripts APIs Government Analytics 93

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 72

Engineering APIs Big data Accountability 72

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 75

Analytics APIs Healthcare Big data 75

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 61

APIs Customer Experience Feedback Chatbots 61

AWS Machine Learning

JUNE 24, 2022

In the initial phase, the goal is to create a secure experimentation environment where the data scientist receives snapshots of data and experiments using SageMaker notebooks to prove that ML can solve a specific business problem. In the same account, Amazon SageMaker Feature Store can be hosted, but we don’t cover it this post.

Enterprise 87

Enterprise Engineering Accountability APIs 87

AWS Machine Learning

AUGUST 15, 2022

Named entity recognition (NER) is a natural language processing (NLP) sub-task that involves sifting through text data to locate noun phrases, called named entities, and categorizing each with a label, such as brand, date, event, location, organizations, person, quantity, or title. The following screenshot shows an example of our entity list.

Banking 74

Banking APIs Accountability Analytics 74

AWS Machine Learning

JANUARY 26, 2024

Lastly, we connect these together with an example LLM workload to describe an approach towards architecting with defense-in-depth security across trust boundaries. In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices.

Best practices 119

Best practices Government Engineering Accountability 119

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 77

APIs Scripts Enterprise Big data 77

AWS Machine Learning

AUGUST 3, 2023

For example, on online shopping platforms, the angle at which products are shown in images has an effect on the rate of buying this product. It can be used for further postprocessing on the image, for example, to crop out the whole car. Prerequisites For this walkthrough, you should have the following prerequisites: An AWS account.

APIs 63

APIs Scripts Engineering Technical Support 63

AWS Machine Learning

AUGUST 2, 2023

As an example, a GenAI model can be used to generate a textual description for the following image as “a dog laying on the ground under an umbrella” during document ingestion of the image. 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.

Enterprise 71

Enterprise Healthcare APIs Big data 71

AWS Machine Learning

DECEMBER 1, 2022

For example, model builders need to proactively record model specifications such as intended use for a model, risk rating, and performance criteria a model should be measured against. datasets=["s3://path/to/evaluation/data"], metric_groups=[my_metric_group], ) ]. The following screenshot shows an example of the Model dashboard.

Government 77

Government Metrics APIs Engineering 77

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 75

Engineering Healthcare APIs Scripts 75

AWS Machine Learning

JULY 19, 2022

For the purpose of our example, we requested the speech mark type as word. 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.

Engineering 84

Engineering APIs Education Best practices 84

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. An example IAM policy for an ML administrator may look like the following code. In this example, we choose Data Scientist.

Management 73

Management Government Enterprise APIs 73

Nicereply

MAY 28, 2020

Let’s take an example with this inquiry: “We just purchased and received 3 devices, when I connect them to our WIFI or LAN they show connected. That might include a software version, account number or additional logs. Let’s take the first two examples from the list illustrated above: Do you deliver to Ireland?

Customer Support 92

Customer Support APIs Big data Personalization 92

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. after adding $4.50

APIs 70

APIs Big data Engineering Sales 70

AWS Machine Learning

JULY 21, 2022

You can also access the trial data via the Python SDK to generate your own visualization using your preferred plotting libraries. To learn more about Experiments APIs and SDKs, we recommend the following documentation: CreateExperiment and Amazon SageMaker Experiments Python SDK. A specific data science and ML project.

Metrics 77

Metrics Scripts Enterprise Telecommunications 77

AWS Machine Learning

MAY 3, 2023

For example, a model predicting direct mail propensity is quite different from a model predicting discount coupon sensitivity of the customers of a Vericast client. Furthermore, SageMaker Processing provides an API interface for running, monitoring, and evaluating the workload.

Engineering 69

Engineering Metrics APIs Big data 69

aircall

APRIL 16, 2021

For example, sales and support teams have been using CRM systems for quite some time. 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. It doesn’t discriminate! Email platforms.

SaaS 62

SaaS Sales Coaching APIs 62

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. Training job steps – An iterative process that teaches a model to make predictions by presenting examples from a training dataset. At the core, this is a regression problem. Prerequisites.

Scripts 72

Scripts Engineering Management APIs 72

Talkdesk

JANUARY 16, 2018

By recognizing your agent heroes as examples to follow, you reinforce their strong performance and encourage them to continue to lead and inspire. 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.

Analytics 40

Analytics Call Center Customer centricity Construction 40

Talkdesk

JANUARY 16, 2018

By recognizing your agent heroes as examples to follow, you reinforce their strong performance and encourage them to continue to lead and inspire. 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.

Analytics 40

Analytics Call Center Customer centricity Construction 40

aircall

MAY 24, 2021

In today’s marketplace, it’s hard to survive without the cloud, big data, APIs, IoT, machine learning, artificial intelligence, automation, and mobile technologies. Software integrations assist on both accounts. Accountability framework. What Is a Digital Transformation Framework? We live and work in the cloud era.

Best practices 62

Best practices Call Center Technology Analytics 62

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 70

APIs Government Accountability Scripts 70

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 79

APIs Engineering Analytics Scripts 79

Enghouse Interactive

JULY 10, 2018

For example, “How do I cancel a lost card?” Here are some examples where members will expect personal and highly relevant interactions: -Financial advice from an expert when researching home loans, or investment planning. Making significant changes to an account. Inquiring about fraud or unfamiliar charges. #3.

Self service 40

Self service CRM Contact Center Analytics 40

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 108

Best practices Engineering SaaS APIs 108

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 87

Government Accountability Enterprise Engineering 87

AWS Machine Learning

AUGUST 29, 2023

Terraform is used to create additional resources such as EventBridge rules, Lambda functions, and SNS topics for monitoring SageMaker pipelines and sending notifications (for example, when a pipeline step fails or succeeds). The central model registry could optionally be placed in a shared services account as well.

Scripts 72

Scripts APIs Enterprise Accountability 72

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. Choose Create rule.

APIs 70

APIs Accountability Construction Enterprise 70

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. For example, [link]. To check, view the data sources and verify if the last sync was successful. Choose Done.

Management 93

Management Enterprise Analytics Finance 93

AWS Machine Learning

JUNE 3, 2024

With a data flow, you can prepare data using generative AI, over 300 built-in transforms, or custom Spark commands. Complete the following steps: Choose Prepare and analyze data. For Data flow name , enter a name (for example, AssessingMentalHealthFlow ). SageMaker Data Wrangler will open. Choose Create.

Surveys 86

Surveys Metrics Analytics Engineering 86

Natalie Petouhof

MAY 25, 2016

For example, because each Halo device is linked to the IOT hub, a person sitting in the bedroom can be alerted of a fire in the kitchen, the exact level of threat it poses, and what needs to be done next. 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

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

AWS Machine Learning

APRIL 19, 2023

For example, a model for a ride-sharing app can choose the best price for a ri­de from the airport, but only if it knows the number of ride requests received in the past 10 minutes and the number of passengers projected to land in the next 10 minutes. For example, we can create and populate a feature group called cc-transactions-fg.

Engineering 77

Engineering Analytics APIs Enterprise 77