AWS Machine Learning

OCTOBER 2, 2024

Provide control through transparency of models, guardrails, and costs using metrics, logs, and traces The control pillar of the generative AI framework focuses on observability, cost management, and governance, making sure enterprises can deploy and operate their generative AI solutions securely and efficiently.

Government 131

Government APIs Enterprise Best practices 131

AWS Machine Learning

SEPTEMBER 9, 2022

This is Part 2 of a series on using data analytics and ML for Amp and creating a personalized show recommendation list platform. The platform has shown a 3% boost to customer engagement metrics tracked (liking a show, following a creator, enabling upcoming show notifications) since its launch in May 2022. Operational health.

Personalization 93

Personalization APIs Metrics Engineering 93

AWS Machine Learning

MAY 3, 2023

The managed cluster, instances, and containers report metrics to Amazon CloudWatch , including usage of GPU, CPU, memory, GPU memory, disk metrics, and event logging. Worse yet, memory could become an issue, resulting in either poor performance or out of memory events causing the entire job to fail.

Engineering 103

Engineering Metrics APIs Big data 103

AWS Machine Learning

FEBRUARY 15, 2024

With the use of cloud computing, big data and machine learning (ML) tools like Amazon Athena or Amazon SageMaker have become available and useable by anyone without much effort in creation and maintenance. The predicted value indicates the expected value for our target metric based on the training data.

Metrics 128

Metrics Analytics APIs Big data 128

AWS Machine Learning

OCTOBER 29, 2024

Amazon SageMaker Model Monitor allows you to automatically monitor ML models in production, and alerts you when data and model quality issues appear. SageMaker Model Monitor emits per-feature metrics to Amazon CloudWatch , which you can use to set up dashboards and alerts. Enable CloudWatch cross-account observability.

Government 113

Government Metrics Accountability APIs 113

AWS Machine Learning

MARCH 15, 2024

When training is complete, choose the System tab to see the training time durations on your edge servers and aggregation events. He entered the big data space in 2013 and continues to explore that area. Choose the Training Status tab and wait for the training run to complete. You can also navigate to the tabs available.

Healthcare 131

Healthcare Big data Engineering Accountability 131

AWS Machine Learning

FEBRUARY 2, 2023

One of the challenges when building predictive models for punt and kickoff returns is the availability of very rare events — such as touchdowns — that have significant importance in the dynamics of a game. Using a robust method to accurately model distribution over extreme events is crucial for better overall performance.

Calibration 95

Calibration Engineering Big data Automotive 95

AWS Machine Learning

OCTOBER 1, 2022

Introducing Pressure Handling, a new Bundesliga Match Fact that aims to evaluate the performance of a frequently pressed player using different metrics. The following heuristic is used for computing the escape rate: We start with a series of pressure events, based on the existing Most Pressed Player Match Fact. Examples of escapes.

Consulting 113

Consulting Consulting Telecommunications Big data 113

AWS Machine Learning

OCTOBER 16, 2024

To evaluate the transcription accuracy quality, the team compared the results against ground truth subtitles on a large test set, using the following metrics: Word error rate (WER) – This metric measures the percentage of words that are incorrectly transcribed compared to the ground truth. A lower MER signifies better accuracy.

Engineering 126

Engineering Metrics APIs Big data 126

AWS Machine Learning

JULY 14, 2022

Before you can begin publishing events from your SageMaker hosted model into Fiddler, you need to create a project within your Fiddler trial environment and provide Fiddler details about your model through a step called model registration. Now you can publish some events to Fiddler in order to observe the model’s performance.

Enterprise 96

Enterprise Engineering Analytics Big data 96

AWS Machine Learning

JULY 29, 2022

Customer satisfaction is a potent metric that directly influences the profitability of an organization. Vamshi Krishna Enabothala is a Senior AI/ML Specialist SA at AWS with expertise in big data, analytics, and orchestrating scalable AI/ML architectures for startups and enterprises. You can follow Prem’s work on LinkedIn.

Contact Center 130

Contact Center Interactive Voice Response Self service Accountability 130

AWS Machine Learning

DECEMBER 18, 2023

The triggers need to be scheduled to write the data to S3 at a period frequency based on the business need for training the models. When the model is ready, select the model and click on the latest version Review the model metrics and column impact and if you are satisfied with the model performance, click Predict.

Finance 131

Finance APIs Analytics Scripts 131

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 91

Analytics Engineering Metrics APIs 91

Calabrio

APRIL 25, 2017

One of the most confounding challenges for modern contact center leaders is reporting on any performance metric that requires information from more than one system or application, each of which is a self-contained silo of data. Historic data. The birth of Big Data. Contact center reporting technology of the future.

Multichannel 56

Multichannel Contact Center Big data Metrics 56

AWS Machine Learning

SEPTEMBER 21, 2022

To achieve this, companies want to understand industry trends and customer behavior, and optimize internal processes and data analyses on a routine basis. When looking at these metrics, business analysts often identify patterns in customer behavior, in order to determine whether the company risks losing the customer. Choose Visualize.

Metrics 97

Metrics Marketing Big data Banking 97

AWS Machine Learning

NOVEMBER 13, 2024

SageMaker Model Registry catalogs your models along with their versions and associated metadata and metrics for training and evaluation. Evaluate your training data for data quality, including feature importance and bias, and update the model package version with relevant evaluation metrics. medium", "ml.m5.large"],

Government 120

Government Engineering Metrics APIs 120

AWS Machine Learning

DECEMBER 1, 2022

With the SageMaker Python SDK, you can seamlessly update the Model card with evaluation metrics. Model cards provide model risk managers, data scientists, and ML engineers the ability to perform the following tasks: Document model requirements such as risk rating, intended usage, limitations, and expected performance.

Government 102

Government Metrics APIs Engineering 102

Totango

SEPTEMBER 1, 2022

In addition to relying on outdated data, the traditional QBR model fails to take advantage of the latest tools for agile innovation in digital technology, AI, and big data analytics. Today’s competitive SaaS company needs a digital, data-driven, AI-powered approach to QBRs for SaaS. Reimagining the SaaS QBR .

SaaS 101

SaaS Journey mapping Upselling Best practices 101

AWS Machine Learning

OCTOBER 27, 2022

We also use AWS Glue to conduct ETL (extract, transform, and load), read data covering the target SKUs across a meaningful time range, and load data to Amazon S3 with an indicated prefix. After data is loaded to Amazon S3, an S3 event triggers AWS Lambda and invokes AWS Step Functions as an orchestration tool.

APIs 98

APIs Best practices Metrics Government 98

AWS Machine Learning

SEPTEMBER 11, 2024

SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. SIMT describes processors that are able to operate on data vectors and arrays (as opposed to just scalars), and therefore handle big data workloads efficiently.

Benchmark 113

Benchmark Banking Analytics Big data 113

AWS Machine Learning

JUNE 24, 2022

The model training step could be either one training job, if the data scientist is aware of the best model configuration, or a hyperparameter optimization (HPO) job, in which AWS defines the best hyperparameters for the model (Bayesian method) and produces the corresponding model artifact.

Enterprise 127

Enterprise Engineering Accountability APIs 127

Aria Solutions

JUNE 8, 2017

Most contact centers use interaction data to justify or support contact center metrics, such as average call handle time, speed of answer, abandonment and even first call resolution. But when you think about it, doesn’t it make more sense to capture data at the event and interaction level?

Contact Center 48

Contact Center Big data First call resolution Metrics 48

AWS Machine Learning

AUGUST 29, 2023

Batch inference The SageMaker batch inference pipeline runs on a schedule (via EventBridge) or based on an S3 event trigger as well. The batch inference pipeline includes steps for checking data quality against a baseline created by the training pipeline, as well as model quality (model performance) if ground truth labels are available.

Scripts 94

Scripts APIs Enterprise Accountability 94

Calabrio

APRIL 25, 2017

One of the most confounding challenges for modern contact center leaders is reporting on any performance metric that requires information from more than one system or application, each of which is a self-contained silo of data. Historic data. The birth of Big Data. Contact center reporting technology of the future.

Multichannel 40

Multichannel Contact Center Big data Metrics 40

Calabrio

APRIL 25, 2017

One of the most confounding challenges for modern contact center leaders is reporting on any performance metric that requires information from more than one system or application, each of which is a self-contained silo of data. Historic data. The birth of Big Data. Contact center reporting technology of the future.

Multichannel 40

Multichannel Contact Center Big data Metrics 40

AWS Machine Learning

APRIL 21, 2023

This step uses the built-in ProcessingStep with the provided code, evaluation.py , to evaluate performance metrics (accuracy, area under curve). Configure the baseline step To monitor the model and data, a baseline is required. Monitoring for data drift requires a baseline of training data. medium', 'ml.m5.xlarge'],

Metrics 110

Metrics Telecommunications Analytics Healthcare 110

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. This automated pipeline can then be triggered by simple events you define, without human intervention. Edge computing. Use case 1.

Transportation 96

Transportation APIs Big data Wireless 96

AWS Machine Learning

MAY 10, 2023

Exploring, analyzing, interpreting, and finding trends in data is essential for businesses to achieve successful outcomes. Business analysts play a pivotal role in facilitating data-driven business decisions through activities such as the visualization of business metrics and the prediction of future events.

Accountability 101

Accountability Enterprise Big data Management 101

CustomerSuccessBox

JUNE 20, 2022

A customer succes software is specialized software that takes the customer data from your existing tech stack to provide you with a 360-degree view of your customers and their account health. In general, this tool offloads the heavy work of tracking and managing all the customer success metrics.

Upselling 52

Upselling SaaS CRM Multi-channel support 52

aircall

MAY 17, 2021

Companies rely heavily on reporting without the advantage of data and analytics that are so critical to establishing efficient, productive workflows. In today’s marketplace, automation, digitization, and big data are your friends. It will lead you to greater operational efficiency and better decision-making.

Transportation 71

Transportation Entertainment voip Construction 71

CustomerSuccessBox

MAY 30, 2022

To identify a watermelon customer, the metric that would help you the most is instead the Customer Intent Score. The Customer Intent Score is a metric that measures a visitor’s willingness to accomplish a conversion goal, for example- a request for further information. Product telemetry data. But what does it tell?

Upselling 52

Upselling Calibration Engineering Big data 52

Xaqt

FEBRUARY 6, 2020

Back then, Artificial Intelligence, APIs, Robotic Process Automation (RPA), and even "Big Data" weren't things yet. Go ask the person in Public Works responsible for managing your street lights what they think about dynamically adjusting the luminosity based on real-time events happening in the parking department.

Contact Center 52

Contact Center Enterprise Call Center APIs 52

JivoChat

FEBRUARY 16, 2022

AI marketing tools can help you in different aspects, for example, to enhance the quality of your content, make data-driven decisions, analyze performance, have new insights, and much more. . The Content Marketing Semrush tool helps you to plan and execute data-driven strategies based on your target audience’s needs. .

Marketing 52

Marketing Advertising Analytics Benchmark 52

aircall

MARCH 19, 2021

With all the available customer data companies have at their disposal to enhance the performance of customer service, sales, and marketing efforts, a remarkable 73% of companies still do not use it effectively. And out of those who do practise data collection, only 12% analyze it. Be Transparent. Where will you store the backups?

Sales 62

Sales CRM Marketing Best practices 62

AWS Machine Learning

NOVEMBER 9, 2023

Policy 6 – Attach CloudWatchEventsFullAccess , which is an AWS managed policy that grants full access to CloudWatch Events. She holds a master’s degree in Computer Science specialized in Data Science from the University of Colorado, Boulder. Data Lake Architect with AWS Professional Services. Sunita Koppar is a Sr.

Scripts 130

Scripts Accountability Best practices Engineering 130

Real Blue Sky

NOVEMBER 16, 2022

Their Early Warning System analyzes over one million events each week to make predictions on car parts that will need to be changed or repaired. In fact, tracking customer sentiment is now such an essential metric that 64% of companies consider following customer sentiment analysis critical for measuring #CX.

Customer Experience 52

Customer Experience Chatbots CRM Analytics 52

Real Blue Sky

NOVEMBER 16, 2022

Their Early Warning System analyzes over one million events each week to make predictions on car parts that will need to be changed or repaired. In fact, tracking customer sentiment is now such an essential metric that 64% of companies consider following customer sentiment analysis critical for measuring #CX.

Customer Experience 52

Customer Experience Chatbots CRM Analytics 52