Accountability, Best practices, Big data and Engineering

Set up cross-account Amazon S3 access for Amazon SageMaker notebooks in VPC-only mode using Amazon S3 Access Points

AWS Machine Learning

MARCH 13, 2024

To develop models for such use cases, data scientists need access to various datasets like credit decision engines, customer transactions, risk appetite, and stress testing. Amazon S3 Access Points simplify managing and securing data access at scale for applications using shared datasets on Amazon S3.

Accountability

Accountability Engineering Enterprise Big data

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

Use AWS PrivateLink to set up private access to Amazon Bedrock

AWS Machine Learning

OCTOBER 30, 2023

The Amazon Bedrock VPC endpoint powered by AWS PrivateLink allows you to establish a private connection between the VPC in your account and the Amazon Bedrock service account. Use the following template to create the infrastructure stack Bedrock-GenAI-Stack in your AWS account. With an M.Sc.

APIs

APIs Big data Accountability Enterprise

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning

NOVEMBER 9, 2023

Central model registry – Amazon SageMaker Model Registry is set up in a separate AWS account to track model versions generated across the dev and prod environments. Approve the model in SageMaker Model Registry in the central model registry account. Create a pull request to merge the code into the main branch of the GitHub repository.

Scripts

Scripts Accountability Engineering Best practices

Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. Another essential component is an orchestration tool suitable for prompt engineering and managing different type of subtasks. A feature store maintains user profile data.

Personalization

Personalization Engineering Construction Transportation

Localize content into multiple languages using AWS machine learning services

AWS Machine Learning

JULY 19, 2022

Before getting started, you must have the following prerequisites: An AWS account. Trusted accounts for deployment: (none) Trusted accounts for lookup: (none) Using default execution policy of 'arn:aws:iam::aws:policy/AdministratorAccess'. He helps them drive their cloud architecture and data strategy using best practices.

Engineering

Engineering APIs Education Best practices

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. get_caller_identity()['Account'] region = boto3.Session().region_name

APIs

APIs Engineering Construction Benchmark

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

AWS Machine Learning

MARCH 23, 2023

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. We perform data exploration and feature engineering using a SageMaker notebook, and then perform model training using a SageMaker training job.

Scripts

Scripts APIs Government Analytics

Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

AWS Machine Learning

OCTOBER 20, 2023

Governing ML lifecycle at scale is a framework to help you build an ML platform with embedded security and governance controls based on industry best practices and enterprise standards. The architecture maps the different capabilities of the ML platform to AWS accounts.

Government

Government Engineering Accountability Enterprise

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

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. 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.

Enterprise

Enterprise Healthcare APIs Big data

How to Improve Digital Customer Experience in Banking

REVE Chat Blog

FEBRUARY 12, 2020

A chatbot is the best channel banks can use to automate their simple and routine tasks (knowing account balance, outstanding credit card amount, how to change the address, etc.) In-app chatbots can access user account details and provide completely personalized information and help or even financial advice based on data. .

Banking

Banking Customer Experience Chatbots 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

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

AWS Machine Learning

APRIL 24, 2023

We’re grateful for the support provided by the AWS account team, solution architecture team, and ML experts from the SSO and service team.” – LC Lee, founder and CEO of Pro360. With 8 years of experience in the IT industry, Ray is dedicated to building modern solutions on the cloud, especially in NoSQL, big data, and machine learning.

APIs

APIs Customer Experience Feedback Chatbots

Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources

AWS Machine Learning

FEBRUARY 28, 2024

Third, despite the larger adoption of centralized analytics solutions like data lakes and warehouses, complexity rises with different table names and other metadata that is required to create the SQL for the desired sources. Athena also allows us to use a multitude of supported endpoints and connectors to cover a large set of data sources.

Engineering

Engineering Best practices Analytics Enterprise

MLOps deployment best practices for real-time inference model serving endpoints with Amazon SageMaker

AWS Machine Learning

FEBRUARY 21, 2023

In addition to choosing the right deployment strategy, that strategy should be implemented using a reliable mechanism that includes MLOps practices. When the model update process is complete, SageMaker Model Monitor continually monitors the model performance for drifts into the model and data quality.

Best practices

Best practices Accountability Metrics Engineering

Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

AWS Machine Learning

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. JuMa is now available to all data scientists, ML engineers, and data analysts at BMW Group.

Engineering

Engineering Analytics Government Self service

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. Depending on your governance requirements, Data Science & Dev accounts can be merged into a single AWS account.

Government

Government Accountability Enterprise Engineering

From CTO to CX Industry Analyst: An In-depth Conversation with Mark Hillary

Vistio

OCTOBER 5, 2021

And you can look at various specific areas such as data analytics, big data, being able to study patterns within data, using artificial intelligence or using machine learning to actually gather up every customer interaction, and remember the original problem and the solution.

Chatbots

Chatbots Contact Center Banking Technology

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. Key accountabilities & responsibilities. Master’s degree.

Engineering

Engineering APIs Analytics Healthcare

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. Depending on your governance requirements, Data Science & Dev accounts can be merged into a single AWS account.

Government

Government Accountability Enterprise Engineering

Automate Amazon SageMaker Pipelines DAG creation

AWS Machine Learning

FEBRUARY 29, 2024

This enables data scientists to quickly build and iterate on ML models, and empowers ML engineers to run through continuous integration and continuous delivery (CI/CD) ML pipelines faster, decreasing time to production for models. Jinzhao Feng , is a Machine Learning Engineer at AWS Professional Services.

Scripts

Scripts Engineering Metrics Best practices

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

AWS Machine Learning

MAY 8, 2023

How to use MLflow as a centralized repository in a multi-account setup. Prerequisites Before deploying the solution, make sure you have access to an AWS account with admin permissions. Multi-account considerations Data science workflows have to pass multiple stages as they progress from experimentation to production.

APIs

APIs Government Accountability Scripts

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

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

Scripts APIs Enterprise Accountability

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

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

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. Consequently, maintaining and augmenting older projects required more engineering time and effort. AWS Secrets Manager to protect secrets needed to access your applications.

Engineering

Engineering Healthcare APIs Scripts

Define customized permissions in minutes with Amazon SageMaker Role Manager

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. Delete the ML administrator role that you created.

Management

Management Government Enterprise APIs

The indispensable role of Customer Success in B2B SaaS with ChurnZero CEO You Mon Tsang

ChurnZero

JUNE 3, 2022

To talk about what needs to change and to offer his thoughts on how you can do it, we’re joined by You Mon Tsang who founded not just one, but four successful software companies, including Biz360, Engine 140, and Milktruck, before going on to found his latest business ChurnZero where he’s CEO and founder. You Mon: Accountability.

SaaS

SaaS B2B Upselling Metrics

The indispensable role of Customer Success in B2B SaaS with ChurnZero CEO You Mon Tsang

ChurnZero

JUNE 3, 2022

To talk about what needs to change and to offer his thoughts on how you can do it, we’re joined by You Mon Tsang who founded not just one, but four successful software companies, including Biz360, Engine 140, and Milktruck, before going on to found his latest business ChurnZero where he’s CEO and founder. You Mon: Accountability.

SaaS

SaaS B2B Upselling Metrics

Marketing & Social Content Writer

Stratifyd

DECEMBER 20, 2018

In this role you will work collaboratively with our Sales, Engineering, and Leadership team to develop meaningful content across multiple channels that drives brand awareness through effective messaging. Key accountabilities & responsibilities. Experience and/or knowledge of AI, Big Data, Tech.

Marketing

Marketing Brand ambassadors Healthcare Scripts

How AWS Prototyping enabled ICL-Group to build computer vision models on Amazon SageMaker

AWS Machine Learning

DECEMBER 14, 2023

ICL is a multi-national manufacturing and mining corporation based in Israel that manufactures products based on unique minerals and fulfills humanity’s essential needs, primarily in three markets: agriculture, food, and engineered materials. He was fortunate to research spatial and time series data in the precision agriculture domain.

Engineering

Engineering Big data outsourcing Education

Best Egg achieved three times faster ML model training with Amazon SageMaker Automatic Model Tuning

AWS Machine Learning

JANUARY 26, 2023

To help you efficiently tune your required hyperparameters and determine the best-performing model, this post will discuss how Best Egg used SageMaker hyperparameter tuning with warm pools and achieved a three-fold improvement in model training time. Best Egg trains multiple credit models using classification and regression algorithms.

Finance

Finance Engineering Big data Banking

Totango: Customer Success Management for a Post-Sale, On-Demand, Attention Economy (Part 1)

Natalie Petouhof

AUGUST 26, 2015

Prior to starting Totango, he worked in the area of real-time Big Data as executive vice president of engineering at GigaSpaces Technologies, a middleware provider. Totango monitors this data to eliminate the guesswork when it comes to understanding customer health and engagement. What Are the Benefits of Using Totango?

Sales

Sales Management Advertising Best practices

Customer Contact Central

Set up cross-account Amazon S3 access for Amazon SageMaker notebooks in VPC-only mode using Amazon S3 Access Points

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

Webinars

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Use AWS PrivateLink to set up private access to Amazon Bedrock

Webinars

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

Personalize your generative AI applications with Amazon SageMaker Feature Store

Localize content into multiple languages using AWS machine learning services

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

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

Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

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

How to Improve Digital Customer Experience in Banking

Designing generative AI workloads for resilience

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

Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources

MLOps deployment best practices for real-time inference model serving endpoints with Amazon SageMaker

Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

Use Amazon SageMaker Model Card sharing to improve model governance

From CTO to CX Industry Analyst: An In-depth Conversation with Mark Hillary

Senior back-end software engineer

Use Amazon SageMaker Model Cards sharing to improve model governance

Automate Amazon SageMaker Pipelines DAG creation

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

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

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

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

Define customized permissions in minutes with Amazon SageMaker Role Manager

The indispensable role of Customer Success in B2B SaaS with ChurnZero CEO You Mon Tsang

The indispensable role of Customer Success in B2B SaaS with ChurnZero CEO You Mon Tsang

Marketing & Social Content Writer

How AWS Prototyping enabled ICL-Group to build computer vision models on Amazon SageMaker

Best Egg achieved three times faster ML model training with Amazon SageMaker Automatic Model Tuning

Totango: Customer Success Management for a Post-Sale, On-Demand, Attention Economy (Part 1)

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