AWS Machine Learning

OCTOBER 28, 2024

Examples include financial systems processing transaction data streams, recommendation engines processing user activity data, and computer vision models processing video frames. A preprocessor script is a capability of SageMaker Model Monitor to preprocess SageMaker endpoint data capture before creating metrics for model quality.

Scripts 104

Scripts Metrics Engineering Analytics 104

AWS Machine Learning

NOVEMBER 26, 2024

Datadog is excited to launch its Neuron integration , which pulls metrics collected by the Neuron SDK’s Neuron Monitor tool into Datadog, enabling you to track the performance of your Trainium and Inferentia based instances. If you don’t already have a Datadog account, you can sign up for a free 14-day trial today.

Metrics 104

Metrics Engineering Sales Marketing 104

AWS Machine Learning

APRIL 3, 2024

Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. Amazon OpenSearch Service now supports the cosine similarity metric for k-NN indexes.

Engineering 125

Engineering Accountability Education Metrics 125

AWS Machine Learning

JANUARY 7, 2025

The solution proposed in this post relies on LLMs context learning capabilities and prompt engineering. The project also requires that the AWS account is bootstrapped to allow the deployment of the AWS CDK stack. Also note the completion metrics on the left pane, displaying latency, input/output tokens, and quality scores.

Engineering 104

Engineering Metrics industry standards Finance 104

AWS Machine Learning

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

Metrics 87

Metrics APIs Engineering Accountability 87

AWS Machine Learning

MARCH 6, 2025

Current RAG pipelines frequently employ similarity-based metrics such as ROUGE , BLEU , and BERTScore to assess the quality of the generated responses, which is essential for refining and enhancing the models capabilities. More sophisticated metrics are needed to evaluate factual alignment and accuracy.

Metrics 83

Metrics Enterprise APIs Engineering 83

AWS Machine Learning

MARCH 27, 2025

This requirement translates into time and effort investment of trained personnel, who could be support engineers or other technical staff, to review tens of thousands of support cases to arrive at an even distribution of 3,000 per category. If the use case doesnt yield discrete outputs, task-specific metrics are more appropriate.

Education 88

Education Engineering APIs Enterprise 88

AWS Machine Learning

MARCH 14, 2025

Although automated metrics are fast and cost-effective, they can only evaluate the correctness of an AI response, without capturing other evaluation dimensions or providing explanations of why an answer is problematic. Human evaluation, although thorough, is time-consuming and expensive at scale.

Metrics 81

Metrics Best practices Engineering APIs 81

AWS Machine Learning

MARCH 25, 2025

The ability to quickly retrieve and analyze session data empowers developers to optimize their applications based on actual usage patterns and performance metrics. Prerequisites To follow along with this post, you need an AWS account with the appropriate permissions. He enjoys playing tennis and biking on mountain trails.

APIs 107

APIs Management Government Healthcare 107

AWS Machine Learning

MAY 3, 2023

One aspect of this data preparation is feature engineering. Feature engineering refers to the process where relevant variables are identified, selected, and manipulated to transform the raw data into more useful and usable forms for use with the ML algorithm used to train a model and perform inference against it.

Engineering 89

Engineering Metrics APIs Big data 89

AWS Machine Learning

NOVEMBER 7, 2024

SageMaker JumpStart is a machine learning (ML) hub that provides a wide range of publicly available and proprietary FMs from providers such as AI21 Labs, Cohere, Hugging Face, Meta, and Stability AI, which you can deploy to SageMaker endpoints in your own AWS account. They’re illustrated in the following figure.

Enterprise 110

Enterprise APIs Government Accountability 110

AWS Machine Learning

FEBRUARY 21, 2025

Compound AI system and the DSPy framework With the rise of generative AI, scientists and engineers face a much more complex scenario to develop and maintain AI solutions, compared to classic predictive AI. DSPy supports iteratively optimizing all prompts involved against defined metrics for the end-to-end compound AI solution.

Benchmark 82

Benchmark Metrics Engineering Feedback 82

AWS Machine Learning

OCTOBER 5, 2022

So much exposure naturally brings added risks like account takeover (ATO). Each year, bad actors compromise billions of accounts through stolen credentials, phishing, social engineering, and multiple forms of ATO. To put it into perspective: account takeover fraud increased by 90% to an estimated $11.4

Accountability 88

Accountability APIs Metrics Engineering 88

AWS Machine Learning

MARCH 25, 2025

Automated safety guards Integrated Amazon CloudWatch alarms monitor metrics on an inference component. AlarmName This CloudWatch alarm is configured to monitor metrics on an InferenceComponent. For more information, check out the SageMaker AI documentation or connect with your AWS account team.

APIs 84

APIs Engineering Accountability Metrics 84

AWS Machine Learning

MARCH 11, 2025

How do Amazon Nova Micro and Amazon Nova Lite perform against GPT-4o mini in these same metrics? Vector database FloTorch selected Amazon OpenSearch Service as a vector database for its high-performance metrics. How well do these models handle RAG use cases across different industry domains? Each provisioned node was r7g.4xlarge,

Benchmark 99

Benchmark APIs Enterprise Scripts 99

AWS Machine Learning

FEBRUARY 21, 2025

We implemented an AWS multi-account strategy, standing up Amazon SageMaker Studio in a build account using a network-isolated Amazon VPC. The solution consists of the following components: Data ingestion: Data is ingested into the data account from on-premises and external sources. Analytic data is stored in Amazon Redshift.

Engineering 70

Engineering Finance Accountability Analytics 70

AWS Machine Learning

NOVEMBER 16, 2022

When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to isolate resources, contain security threats and simplify billing-and data science pipelines are no different. Some things to note in the preceding architecture: Accounts follow a principle of least privilege to follow security best practices.

Accountability 96

Accountability Best practices Scripts Engineering 96

AWS Machine Learning

JULY 31, 2023

It also enables you to evaluate the models using advanced metrics as if you were a data scientist. In this post, we show how a business analyst can evaluate and understand a classification churn model created with SageMaker Canvas using the Advanced metrics tab. The F1 score provides a balanced evaluation of the model’s performance.

Metrics 95

Metrics Engineering Accountability Telecommunications 95

AWS Machine Learning

FEBRUARY 25, 2025

Amazon Q Business only provides metric information that you can use to monitor your data source sync jobs. Prerequisites For this walkthrough, you should have the following prerequisites: An AWS account Access to the Alation service with the ability to create new policies and access tokens.

Enterprise 89

Enterprise Engineering APIs Accountability 89

AWS Machine Learning

JUNE 13, 2022

We are excited to launch a causal contribution analysis capability in Amazon Lookout for Metrics that helps you to understand the potential root causes for the business-critical anomalies in the data. Lookout for Metrics reduces the time to implement AI/ML services for business-critical problems.

Metrics 95

Metrics Advertising Telecommunications Engineering 95

AWS Machine Learning

FEBRUARY 5, 2025

Previously, OfferUps search engine was built with Elasticsearch (v7.10) on Amazon Elastic Compute Cloud (Amazon EC2), using a keyword search algorithm to find relevant listings. These challenges include: Context understanding Keyword searches dont account for the context in which a term is used.

Engineering 76

Engineering Metrics Analytics Marketing 76

AWS Machine Learning

JUNE 20, 2024

Additionally, evaluation can identify potential biases, hallucinations, inconsistencies, or factual errors that may arise from the integration of external sources or from sub-optimal prompt engineering. This makes it difficult to apply standard evaluation metrics like BERTScore ( Zhang et al.

Metrics 132

Metrics Engineering Accountability Benchmark 132

AWS Machine Learning

FEBRUARY 12, 2025

Prerequisites To build the solution yourself, there are the following prerequisites: You need an AWS account with an AWS Identity and Access Management (IAM) role that has permissions to manage resources created as part of the solution (for example AmazonSageMakerFullAccess and AmazonS3FullAccess ).

Scripts 76

Scripts Metrics Engineering Accountability 76

Outsource Consultants

FEBRUARY 18, 2025

Proactive quality control is the engine that powers this positive cycle. This fosters a sense of shared ownership and accountability. Regular Meetings: Conduct regular business reviews to track progress on action plans, discuss performance metrics, and address any roadblocks that may arise.

Feedback 67

Feedback Customer centricity Best practices Engineering 67

AWS Machine Learning

NOVEMBER 15, 2024

Recall@5 is a specific metric used in information retrieval evaluation, including in the BEIR benchmark. Breanne holds a Bachelor of Science in Computer Engineering from University of Illinois at Urbana Champaign. If so, skip to the next section in this post. Deployment starts when you choose the Deploy option.

Benchmark 104

Benchmark Enterprise Construction Engineering 104

AWS Machine Learning

AUGUST 26, 2024

Our field organization includes customer-facing teams (account managers, solutions architects, specialists) and internal support functions (sales operations). Personalized content will be generated at every step, and collaboration within account teams will be seamless with a complete, up-to-date view of the customer.

Sales 123

Sales Accountability Feedback Metrics 123

ChurnZero

MARCH 24, 2025

Every trend points to customer success becoming the growth engine of businesses, and since customer success typically owns NRR (net revenue retention) , tracking how the teams investments impact performance is also part of that need. 1: You notice your CRM holding your team back. Meetings or calls with that hard-to-reach customer.

Technology 52

Technology CRM Engineering Finance 52

AWS Machine Learning

JANUARY 12, 2023

This is guest post by Andy Whittle, Principal Platform Engineer – Application & Reliability Frameworks at The Very Group. However, this can mean processing customer data in the form of personally identifiable information (PII) in relation to activities such as purchases, returns, use of flexible payment options, and account management.

Engineering 125

Engineering APIs Accountability Metrics 125

Totango

JULY 17, 2024

Three tricks we used to accomplish this include: Be RACI: Using a responsibility assignment matrix (aka a RACI—Responsible, Accountable, Consulted, Informed—matrix) has helped us to clearly define the roles and responsibilities between our CS and sales teams. At the same time, you can build out new opportunities to drive that value.

Sales 100

Sales Metrics Accountability Benchmark 100

ChurnZero

MARCH 28, 2025

The most important mindset shift I made as a CRO is recognizing that CS isnt a revenue centerits a value engine. The metrics were great. Had I not also sat down with the CS team, I would have missed a lot of the factors that allowed us to have that metric. Revenue is the outcome, not the input.

CRM 52

CRM Sales Metrics Upselling 52

AWS Machine Learning

JULY 10, 2024

This process enhances task-specific model performance, allowing the model to handle custom use cases with task-specific performance metrics that meet or surpass more powerful models like Anthropic Claude 3 Sonnet or Anthropic Claude 3 Opus. Under Output data , for S3 location , enter the S3 path for the bucket storing fine-tuning metrics.

APIs 129

APIs Airlines Metrics Engineering 129

AWS Machine Learning

FEBRUARY 5, 2025

About the Authors Nick Biso is a Machine Learning Engineer at AWS Professional Services. He solves complex organizational and technical challenges using data science and engineering. In addition, he builds and deploys AI/ML models on the AWS Cloud. His passion extends to his proclivity for travel and diverse cultural experiences.

Engineering 70

Engineering Feedback Analytics Education 70

AWS Machine Learning

FEBRUARY 1, 2024

There are unique considerations when engineering generative AI workloads through a resilience lens. If you’re performing prompt engineering, you should persist your prompts to a reliable data store. In the low-latency case, you need to account for the time it takes to generate the embedding vectors.

Best practices 134

Best practices Engineering SaaS Accountability 134

Balto

MARCH 3, 2025

These systems manage basic tasks like appointment scheduling, payment processing, and account inquiries without human intervention. Smart routing systems direct calls to the most qualified agents based on skills, availability, and past performance metrics. This creates a more efficient workflow and reduces customer wait times.

Call Center 52

Call Center Interactive Voice Response Average Handle Time First call resolution 52

AWS Machine Learning

JULY 25, 2024

The node recovery agent is a separate component that periodically checks the Prometheus metrics exposed by the node problem detector. Additionally, the node recovery agent will publish Amazon CloudWatch metrics for users to monitor and alert on these events. You can see the CloudWatch NeuronHasError_DMA_ERROR metric has the value 1.

Construction 110

Construction Metrics Scripts Engineering 110

AWS Machine Learning

MAY 13, 2024

In this part of the blog series, we review techniques of prompt engineering and Retrieval Augmented Generation (RAG) that can be employed to accomplish the task of clinical report summarization by using Amazon Bedrock. Prompt engineering helps to effectively design and improve prompts to get better results on different tasks with LLMs.

Healthcare 129

Healthcare Engineering APIs Benchmark 129

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. Solution overview The proposed framework code starts by reading the configuration files. The model_unit.py

Scripts 116

Scripts Engineering Metrics Best practices 116