APIs, Big data, Management and Presentation

Use Amazon SageMaker pipeline sharing to view or manage pipelines across AWS accounts

AWS Machine Learning

AUGUST 29, 2022

You can now use cross-account support for Amazon SageMaker Pipelines to share pipeline entities across AWS accounts and access shared pipelines directly through Amazon SageMaker API calls. Customers are increasingly adopting multi-account architectures for deploying and managing machine learning (ML) workflows with SageMaker Pipelines.

Accountability

Accountability APIs Management Engineering

Secure Amazon SageMaker Studio presigned URLs Part 1: Foundational infrastructure

AWS Machine Learning

JUNE 30, 2022

You can access Amazon SageMaker Studio notebooks from the Amazon SageMaker console via AWS Identity and Access Management (IAM) authenticated federation from your identity provider (IdP), such as Okta. This presents an undesired threat vector for exfiltration and gaining access to customer data when proper access controls are not enforced.

APIs

APIs Enterprise Big data Accountability

La maturità del Customer Experience Management

Quadient

JULY 21, 2022

La maturità del Customer Experience Management. Questo esige che le comunicazioni con i clienti e le interazioni digitali nascano da una strategia centralizzata di Customer Experience Management (CXM), che sia a sua volta basata su una comprensione a 360 gradi del modo in cui i clienti pensano, si sentono e si comportano. j.shah-thiel.

Customer Experience

Customer Experience Management APIs Big data

6 Online Data Analyst Courses

JivoChat

JANUARY 31, 2023

The Data Analyst Course With the Data Analyst Course, you will be able to become a professional in this area, developing all the necessary skills to succeed in your career. The course also teaches beginner and advanced Python, basics and advanced NumPy and Pandas, and data visualization.

Analytics

Analytics APIs Scripts Big data

Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

AWS Machine Learning

AUGUST 3, 2023

Amazon Rekognition is a fully managed service that can perform CV tasks like object detection, video segment detection, content moderation, and more to extract insights from data without the need of any prior ML experience. Training ML algorithms for pose estimation requires a lot of expertise and custom training data.

APIs

APIs Scripts Engineering Technical Support

How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost

AWS Machine Learning

JULY 24, 2023

Patsnap provides a global one-stop platform for patent search, analysis, and management. They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. Build your own container The container’s file directory is presented in the following code. gpt2 and predictor.py

APIs

APIs Engineering Construction Benchmark

How AI can help you deliver an 11-star customer experience

Hello Customer

JUNE 21, 2023

It all starts with data: Data mesh principle AI is more than just machine learning and algorithms. AI represents a complete flow that starts with the data, which gets put in the algorithm and eventually presented to the end-user. That’s where the concept of data mesh comes into play.

Customer Experience

Customer Experience Engineering Feedback Finance

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

AUGUST 2, 2023

Fine-tuning the model on custom fashion data such as fashion images along with text describing the attributes of fashion products can be used to generate metadata that then improves a user’s search experience. Marketing – Another use case of image search is digital asset management.

Enterprise

Enterprise Healthcare APIs Big data

Use a generative AI foundation model for summarization and question answering using your own data

AWS Machine Learning

JULY 19, 2023

When that job is done, you can invoke an API that summarizes the text or answers questions about it. Randy has held a variety of positions in the technology space, ranging from software engineering to product management. In entered the Big Data space in 2013 and continues to explore that area.

Construction

Construction APIs Big data Engineering

BI with an IQ - Revisited

Xaqt

FEBRUARY 6, 2020

Back in the winter of 2005, Jason Kolb (my cofounder and CTO of Latigent) and I penned an article for Business Management magazine titled BI with an IQ. Back then, Artificial Intelligence, APIs, Robotic Process Automation (RPA), and even "Big Data" weren't things yet. technologies were first emerging. Don't believe me?

Contact Center

Contact Center Enterprise Call Center APIs

Reduce cost and development time with Amazon SageMaker Pipelines local mode

AWS Machine Learning

OCTOBER 4, 2022

After the pipeline has been fully tested locally, you can easily rerun it with Amazon SageMaker managed resources with just a few lines of code changes. One of the main drivers for new innovations and applications in ML is the availability and amount of data along with cheaper compute options. Overview of the ML lifecycle.

Scripts

Scripts Engineering Management APIs

Model management for LoRA fine-tuned models using Llama2 and Amazon SageMaker

AWS Machine Learning

NOVEMBER 14, 2023

In the era of big data and AI, companies are continually seeking ways to use these technologies to gain a competitive edge. At the core of these cutting-edge solutions lies a foundation model (FM), a highly advanced machine learning model that is pre-trained on vast amounts of data.

Management

Management APIs Best practices Calibration

Intelligently search Adobe Experience Manager content using Amazon Kendra

AWS Machine Learning

SEPTEMBER 6, 2023

With Amazon Kendra, you can easily aggregate content from a variety of content repositories into an index that lets you quickly search all your enterprise data and find the most accurate answer. Adobe Experience Manager (AEM) is a content management system that’s used for creating website or mobile app content. and above).

Management

Management Enterprise Analytics Finance

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning

DECEMBER 18, 2023

The absence of real-time forecasts in various industries presents pressing business challenges that can significantly impact decision-making and operational efficiency. In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution.

Finance

Finance APIs Analytics Scripts

Designing generative AI workloads for resilience

AWS Machine Learning

FEBRUARY 1, 2024

Because the interface between agents and tools is less formally defined than an API contract, you should monitor these traces not only for performance but also to capture new error scenarios. Randy has held a variety of positions in the technology space, ranging from software engineering to product management.

Best practices

Best practices Engineering SaaS APIs

CREATING CREDIT UNION MEMBERS FOR LIFE

Enghouse Interactive

JULY 10, 2018

By selecting Enghouse Interactive Communications Center (CC) and Quality Management Suite (QMS), Partner Colorado Credit Union found a solution that was intuitive, highly functional, reliable and that provided visibility into each touchpoint of the member experience. In the contact center it all comes down to interactions.

Self service

Self service CRM Contact Center Analytics

Join Us This Summer for WebinarStock!

Callminer

JULY 15, 2019

This year CallMiner is presenting our first annual WebinarStock, July 23rd through 25th. Creating Customer Service Super Agents with Data, Tech and Coaching featuring Forrester. This is a great opportunity to listen, watch, and learn the latest CX analytics information out there! Register for 10am BST Session.

Telecommunications

Telecommunications Contact Center Analytics Employee engagement

Four approaches to manage Python packages in Amazon SageMaker Studio notebooks

AWS Machine Learning

MARCH 7, 2023

This post presents and compares options and recommended practices on how to manage Python packages and virtual environments in Amazon SageMaker Studio notebooks. A public GitHub repo provides hands-on examples for each of the presented approaches. For more information, see Use Amazon SageMaker Studio Notebooks.)

Management

Management Scripts Government Engineering

Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

JANUARY 4, 2024

NLP SQL enables business users to analyze data and get answers by typing or speaking questions in natural language, such as the following: “Show total sales for each product last month” “Which products generated more revenue?” In entered the Big Data space in 2013 and continues to explore that area. Nitin Eusebius is a Sr.

Best practices

Best practices Enterprise Engineering APIs

Team and user management with Amazon SageMaker and AWS SSO

AWS Machine Learning

JULY 29, 2022

Each onboarded user in Studio has their own dedicated set of resources, such as compute instances, a home directory on an Amazon Elastic File System (Amazon EFS) volume, and a dedicated AWS Identity and Access Management (IAM) execution role. Organizations manage their users in AWS SSO instead of the SageMaker domain.

Management

Management APIs Accountability Construction

Generate images from text with the stable diffusion model on Amazon SageMaker JumpStart

AWS Machine Learning

NOVEMBER 7, 2022

We explore two ways of obtaining the same result: via JumpStart’s graphical interface on Amazon SageMaker Studio , and programmatically through JumpStart APIs. If you want to jump straight into the JumpStart API code we go through in this post, you can refer to the following sample Jupyter notebook: Introduction to JumpStart – Text to Image.

APIs

APIs Scripts Enterprise Big data

Run image segmentation with Amazon SageMaker JumpStart

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

APIs Scripts Enterprise Big data

Run text generation with GPT and Bloom models on Amazon SageMaker JumpStart

AWS Machine Learning

NOVEMBER 7, 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 inference, both via the Studio UI and via JumpStart APIs. JumpStart overview. Solution overview.

APIs

APIs Scripts Enterprise Big data

Demystifying machine learning at the edge through real use cases

AWS Machine Learning

JUNE 15, 2022

Edge is a term that refers to a location, far from the cloud or a big data center, where you have a computer device (edge device) capable of running (edge) applications. When you scale your system, it’s important to have a robust solution that can manage the number of devices that you need to support. Edge computing.

Transportation

Transportation APIs Big data Wireless

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

AWS Machine Learning

AUGUST 29, 2023

The presented MLOps workflow provides a reusable template for managing the ML lifecycle through automation, monitoring, auditability, and scalability, thereby reducing the complexities and costs of maintaining batch inference workloads in production.

Scripts

Scripts APIs Enterprise Accountability

Improve governance of your machine learning models with Amazon SageMaker

AWS Machine Learning

DECEMBER 1, 2022

A well-implemented model governance framework should minimize the number of interfaces required to view, track, and manage lifecycle tasks to make it easier to monitor the ML lifecycle at scale. Upload and share model and data evaluation results. Access the Model card hub from the AWS Management Console.

Government

Government Metrics APIs Engineering

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

AWS Machine Learning

JULY 25, 2022

Instead of coercing these graph datasets into tables or sequences, you can use graph ML algorithms to both represent and learn from the data as presented in its graph form, including information about constituent nodes, edges, and other features. For production, we wanted to invoke the model as a simple API call.

Scripts

Scripts Engineering Analytics APIs

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

SEPTEMBER 9, 2022

Its electronic health records, revenue cycle management, and patient engagement tools allow anytime, anywhere access, driving better financial outcomes for its customers and enabling its provider customers to deliver better quality care. Amazon CloudWatch for persistent log management.

Engineering

Engineering Healthcare APIs Scripts

Organize your machine learning journey with Amazon SageMaker Experiments and Amazon SageMaker Pipelines

AWS Machine Learning

JULY 21, 2022

The Pipelines native integration with Experiments makes it easy to automatically track and manage experiments across pipeline runs. SageMaker Experiments allows data scientists organize, track, compare, and evaluate their training iterations. Benefits of SageMaker Experiments.

Metrics

Metrics Scripts Enterprise Telecommunications

Rule-Based Automation Is Out: Intelligent Automation Is In!

SmartKarrot

NOVEMBER 23, 2021

Also known as cognitive intelligence, IA makes use of artificial intelligence (AI), business process management (BPM), and Robotic process automation (RPA) to automate manual and repeatable tasks to achieve efficiency. Business Process Management (BPM). Interpret big data. Like what you are reading? contact-form-7].

Calibration

Calibration Automotive Big data Chatbots

Run machine learning enablement events at scale using AWS DeepRacer multi-user account mode

AWS Machine Learning

SEPTEMBER 21, 2022

With AWS DeepRacer multi-user account management , event organizers can provide hundreds of participants access to AWS DeepRacer using a single AWS account, simplifying event management and improving the participant experience. Build a solution around AWS DeepRacer multi-user account management.

Accountability

Accountability APIs Enterprise Big data

Customer Contact Central

Use Amazon SageMaker pipeline sharing to view or manage pipelines across AWS accounts

Secure Amazon SageMaker Studio presigned URLs Part 1: Foundational infrastructure

Trending Sources

La maturità del Customer Experience Management

6 Online Data Analyst Courses

Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost

How AI can help you deliver an 11-star customer experience

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

Use a generative AI foundation model for summarization and question answering using your own data

BI with an IQ - Revisited

Reduce cost and development time with Amazon SageMaker Pipelines local mode

Model management for LoRA fine-tuned models using Llama2 and Amazon SageMaker

Intelligently search Adobe Experience Manager content using Amazon Kendra

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

Designing generative AI workloads for resilience

CREATING CREDIT UNION MEMBERS FOR LIFE

Join Us This Summer for WebinarStock!

Four approaches to manage Python packages in Amazon SageMaker Studio notebooks

Generating value from enterprise data: Best practices for Text2SQL and generative AI

Team and user management with Amazon SageMaker and AWS SSO

Generate images from text with the stable diffusion model on Amazon SageMaker JumpStart

Run image segmentation with Amazon SageMaker JumpStart

Run text generation with GPT and Bloom models on Amazon SageMaker JumpStart

Demystifying machine learning at the edge through real use cases

MLOps for batch inference with model monitoring and retraining using Amazon SageMaker, HashiCorp Terraform, and GitLab CI/CD

Improve governance of your machine learning models with Amazon SageMaker

Developing advanced machine learning systems at Trumid with the Deep Graph Library for Knowledge Embedding

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

Organize your machine learning journey with Amazon SageMaker Experiments and Amazon SageMaker Pipelines

Rule-Based Automation Is Out: Intelligent Automation Is In!

Run machine learning enablement events at scale using AWS DeepRacer multi-user account mode

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