APIs, Best practices, Big data and Engineering

Use AWS PrivateLink to set up private access to Amazon Bedrock

AWS Machine Learning

OCTOBER 30, 2023

It allows developers to build and scale generative AI applications using FMs through an API, without managing infrastructure. You can choose from various FMs from Amazon and leading AI startups such as AI21 Labs, Anthropic, Cohere, and Stability AI to find the model that’s best suited for your use case.

APIs

APIs Big data Accountability Enterprise

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

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

Best practices Government Engineering Accountability

How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker

AWS Machine Learning

SEPTEMBER 9, 2022

Our initial ML model uses 21 batch features computed daily using data captured in the past 2 months. This data includes both playback and app engagement history per user, and grows with the number of users and frequency of app usage. The processing infrastructure is needed only for the duration of the computations. Real-time inference.

Personalization

Personalization APIs Engineering Metrics

Identify objections in customer conversations using Amazon Comprehend to enhance customer experience without ML expertise

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

APIs Customer Experience Feedback Chatbots

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

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. They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. implement the model and the inference API. gpt2 and predictor.py

APIs

APIs Engineering Construction Benchmark

How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

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. Data Engineer for Amp on Amazon.

Analytics

Analytics Engineering APIs Metrics

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

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

Scripts APIs Government Analytics

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

AWS Machine Learning

JANUARY 4, 2024

In this post, we provide an introduction to text to SQL (Text2SQL) and explore use cases, challenges, design patterns, and best practices. Today, a large amount of data is available in traditional data analytics, data warehousing, and databases, which may be not easy to query or understand for the majority of organization members.

Best practices

Best practices Enterprise Engineering APIs

Localize content into multiple languages using AWS machine learning services

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. Anil Kodali is a Solutions Architect with Amazon Web Services.

Engineering

Engineering APIs Education Best practices

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

AWS Machine Learning

AUGUST 2, 2023

After ingestion, images can be searched via the Amazon Kendra search console, API, or SDK. The image repository is then indexed by Amazon Kendra, which is a search engine that can be used to search for structured and unstructured data. About the Authors Charalampos Grouzakis is a Data Scientist within AWS Professional Services.

Enterprise

Enterprise Healthcare APIs Big data

Designing generative AI workloads for resilience

AWS Machine Learning

FEBRUARY 1, 2024

There are unique considerations when engineering generative AI workloads through a resilience lens. Make sure to validate prompt input data and prompt input size for allocated character limits that are defined by your model. If you’re performing prompt engineering, you should persist your prompts to a reliable data store.

Best practices

Best practices Engineering SaaS 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. tar czvf model.tar.gz -C deepspeed.

Management

Management APIs Best practices Calibration

Securing MLflow in AWS: Fine-grained access control with AWS native services

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.

APIs

APIs Government Accountability Scripts

What’s All This Fuss About Composability?

ConvergeOne

DECEMBER 7, 2021

The underlying technologies of composability include some combination of artificial intelligence (AI), machine learning, automation, container-based architecture, big data, analytics, low-code and no-code development, Agile/DevOps deployment, cloud delivery, and applications with open APIs (microservices).

APIs

APIs Big data Analytics Engineering

Senior back-end software engineer

Stratifyd

JANUARY 3, 2019

We are seeking an analytical, results-driven individual with a passion for developing applications and improving existing ones who knows how to get things done and is not afraid to take on big challenges. As a Senior Back-End Software Engineer with Stratifyd, Inc. Maintain and develop Stratifyd’s API layer and/or analytics pipeline.

Engineering

Engineering APIs Analytics Healthcare

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

AWS Machine Learning

APRIL 19, 2023

This post walks through a complete example of how you can couple streaming feature engineering with Feature Store to make ML-backed decisions in near-real time. Apache Flink is a popular framework and engine for processing data streams. cc_num trans_time amount fraud_label …1248 Nov-01 14:50:01 10.15

Engineering

Engineering Analytics APIs Enterprise

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

AWS Machine Learning

AUGUST 29, 2023

Refer to Operating model for best practices regarding a multi-account strategy for ML. When a new version of the model is registered in the model registry, it triggers a notification to the responsible data scientist via Amazon SNS. The central model registry could optionally be placed in a shared services account as well.

Scripts

Scripts APIs Enterprise Accountability

Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

In addition to data engineers and data scientists, there have been inclusions of operational processes to automate & streamline the ML lifecycle. He is a builder who enjoys helping customers accomplish their business needs and solve complex challenges with AWS solutions and best practices.

Government

Government Accountability Enterprise Engineering

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. How do I eliminate the need of installing a big framework like TensorFlow or PyTorch on my restricted device? Edge computing. or Where is tool B?

Transportation

Transportation APIs Big data Wireless

Call Center Reporting - A New Paradigm

Xaqt

JUNE 22, 2020

Despite significant advancements in big data and open source tools, niche Contact Center Business Intelligence providers are still wed to their own proprietary tools leaving them saddled with technical debt and an inability to innovate from within. Together, we can develop best practices and sharable templates for the entire industry.

Call Center

Call Center Contact Center Analytics Engineering

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

AWS Machine Learning

SEPTEMBER 9, 2022

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. Consequently, maintaining and augmenting older projects required more engineering time and effort.

Engineering

Engineering Healthcare APIs Scripts

Use Amazon SageMaker Model Cards sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

In addition to data engineers and data scientists, there have been inclusions of operational processes to automate & streamline the ML lifecycle. He is a builder who enjoys helping customers accomplish their business needs and solve complex challenges with AWS solutions and best practices.

Government

Government Accountability Enterprise Engineering

Define customized permissions in minutes with Amazon SageMaker Role Manager

AWS Machine Learning

DECEMBER 1, 2022

The statement labeled RemoveErrorMessagesFromConsole can be removed without affecting the ability to get into Studio, but will result in API errors on the console UI. An example IAM policy for an ML administrator may look like the following code. Note that the following policy locks down Studio domain creation to VPC only.

Management

Management Government Enterprise APIs

Customer Contact Central

Use AWS PrivateLink to set up private access to Amazon Bedrock

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Trending Sources

How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker

Identify objections in customer conversations using Amazon Comprehend to enhance customer experience without ML expertise

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

How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

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

Localize content into multiple languages using AWS machine learning services

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

Designing generative AI workloads for resilience

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

Securing MLflow in AWS: Fine-grained access control with AWS native services

What’s All This Fuss About Composability?

Senior back-end software engineer

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

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

Use Amazon SageMaker Model Card sharing to improve model governance

Demystifying machine learning at the edge through real use cases

Call Center Reporting - A New Paradigm

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

Use Amazon SageMaker Model Cards sharing to improve model governance

Define customized permissions in minutes with Amazon SageMaker Role Manager

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