AWS Machine Learning

MAY 5, 2023

For example, searching for the terms “How to orchestrate ETL pipeline” returns results of architecture diagrams built with AWS Glue and AWS Step Functions. Therefore, users without ML expertise can enjoy the benefits of a custom labels model through an API call, because a significant amount of overhead is reduced.

Engineering 102

Engineering APIs Scripts Enterprise 102

ChurnZero

MARCH 18, 2022

With so many SaaS metrics floating around, and even more opinions on when and how to use them, it can be hard to know if you’re measuring what really matters. all the metrics your CEO and CFO care about) and set the context for their usage. all the metrics your CEO and CFO care about) and set the context for their usage.

SaaS 98

SaaS Metrics Enterprise Surveys 98

Help Scout

APRIL 27, 2021

Understanding and managing the power of the queue is critical to a sustainable customer service organization. How will you know if you’ve chosen a good approach? Why “manage the support queue” at all? That certainly would appear fair and effective, but a well-managed queue can do more than that for you and your team.

Management 117

Management Self service Technical Support APIs 117

JustCall

APRIL 5, 2023

The need for customer success management is fairly new and fast becoming pertinent. Organizations need to embrace the CSM approach to build a trustworthy relationship with customers and track their performance using customer relationship management analytics. What is customer success management or CSM?

Management 52

Management CRM Analytics Customer retention 52

AWS Machine Learning

NOVEMBER 22, 2023

Delegating complex AI tasks – You can enable faster AI adoption in your organization by offloading the ML model development lifecycle to managed services and taking advantage of the model development and infrastructure provided by AWS. In the following sections, we discuss how to address common challenges in regards to technical focus areas.

APIs 96

APIs Metrics Enterprise Benchmark 96

AWS Machine Learning

NOVEMBER 8, 2023

We have developed a MONAI Deploy connector to AHI to integrate medical imaging AI applications with subsecond image retrieval latencies at scale powered by cloud-native APIs. The MONAI AI models and applications can be hosted on Amazon SageMaker , which is a fully managed service to deploy machine learning (ML) models at scale.

Healthcare 99

Healthcare APIs Enterprise Engineering 99

AWS Machine Learning

NOVEMBER 17, 2022

Their production segment is therefore an integral building block for delivering on their mission—with a clearly stated ambition to become world-leading on metrics such as safety, environmental footprint, quality, and production costs. However, there is often a lack of solid references for what good performance looks like and how to get there.

APIs 92

APIs Accountability Metrics Engineering 92

AWS Machine Learning

APRIL 17, 2023

Moreover, we discuss how by using Amazon Fraud Detector stored events, you can review results and correctly label the events to retrain your models, thereby improving the effectiveness of fraud prevention measures over time. The following table defines these metrics. AUC uncertainty interval > 0.3

APIs 72

APIs Government Metrics Engineering 72

AWS Machine Learning

APRIL 18, 2024

Check out the following demo to see how it works. In this post, we show you how to use LMA with Amazon Transcribe , Amazon Bedrock , and Knowledge Bases for Amazon Bedrock. When you’re done, you’ll wonder how you ever managed without it! We show you how to use both options in the following sections.

APIs 113

APIs Accountability Analytics Entertainment 113

AWS Machine Learning

DECEMBER 1, 2022

You can then compare the performance of the two versions using metrics such as latency and error rate. Optionally, you can monitor the variants through a built-in dashboard with a side-by-side comparison of the performance metrics. Scenario 1 – Managed shadow testing using the SageMaker Console.

APIs 78

APIs Metrics Management Engineering 78

AWS Machine Learning

MARCH 1, 2023

Amazon Comprehend is a managed AI service that uses natural language processing (NLP) with ready-made intelligence to extract insights about the content of documents. Flywheel creates a data lake (in Amazon S3) in your account where all the training and test data for all versions of the model are managed and stored.

APIs 68

APIs Metrics Accountability Scripts 68

AWS Machine Learning

MAY 24, 2023

In Part 2, we demonstrate how to train and host a computer vision model for tampering detection and localization on Amazon SageMaker. In Part 3, we show how to automate detecting fraud in mortgage documents with an ML model and business-defined rules using Amazon Fraud Detector.

APIs 70

APIs Metrics Management Personalization 70

AWS Machine Learning

FEBRUARY 15, 2024

In this post, we show you how to use SageMaker Canvas to curate and select the right features in your data, and then train a prediction model for anomaly detection, using the no-code functionality of SageMaker Canvas for model tuning. The MLOps expert user has access to a SageMaker notebook and the AWS Management Console.

Metrics 95

Metrics Analytics APIs Big data 95

AWS Machine Learning

MARCH 27, 2024

We discuss how to prepare your data for the model fine-tuning task and how to create a model customization job in Amazon Bedrock. Finally, we show you how to test and deploy your fine-tuned model with Provisioned Throughput. The data remains in the same Region where the API call is processed.

APIs 90

APIs Accountability Engineering Entertainment 90

AWS Machine Learning

OCTOBER 27, 2022

They faced two challenges: how to reduce food waste, and how to manage forecast models for over 10,000 SKUs and thousands of stores efficiently and at scale. A large number of items can cause model management issues for traditional algorithms such as ARIMA, which are configured for each item. Inventory forecasting.

APIs 97

APIs Best practices Metrics Government 97

AWS Machine Learning

NOVEMBER 21, 2023

We show you how to train a MATLAB machine learning model as a SageMaker training job and then deploy the model as a SageMaker real-time endpoint so it can process live, streaming data. This example will summarize each step, providing a practical understanding of how to leverage MATLAB and Amazon SageMaker for machine learning tasks.

Engineering 91

Engineering APIs Scripts Automotive 91

AWS Machine Learning

DECEMBER 12, 2022

Amazon Comprehend provides customized features, custom entity recognition , custom classification , and pre-trained APIs such as key phrase extraction, sentiment analysis, entity recognition, and more so you can easily integrate NLP into your applications. You can use the API operations discussed in this notebook in your own applications.

APIs 75

APIs Accountability Enterprise Metrics 75

AWS Machine Learning

OCTOBER 10, 2022

GrabDefence (GD), Grab’s proprietary fraud detection and prevention technology, and AWS have launched GDxAFD, a fraud detection solution tailored for mobile apps that integrates GD’s device intelligence capabilities with Amazon Fraud Detector , AWS’s fully managed ML fraud detection solution.

APIs 70

APIs Accountability Metrics Government 70

JustCall

JANUARY 23, 2024

A ticketing system, in general terms, refers to an IT support system that allows companies to manage, track, expedite, and resolve issues efficiently. The WhatsApp ticketing system tool allows sales and customer support teams to register, process, manage, and track customer requests through the WhatsApp platform.

APIs 52

APIs Chatbots Multichannel Accountability 52

AWS Machine Learning

NOVEMBER 22, 2023

The IDP Well-Architected Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for guidance on how to build secure, efficient, and reliable IDP solutions on AWS. Pursue Metrics-Driven Quality and Continuous Improvement In IDP, what gets measured gets improved.

Best practices 88

Best practices Metrics Feedback Enterprise 88

AWS Machine Learning

APRIL 24, 2023

Amazon Comprehend is a fully managed and continuously trained natural language processing (NLP) service that can extract insight about the content of a document or text. The steps are as follows: The client side calls Amazon API Gateway as the entry point to provide a client message as input. API Gateway bypasses the request to Lambda.

APIs 62

APIs Customer Experience Feedback Chatbots 62

AWS Machine Learning

NOVEMBER 3, 2022

In Part 1 of this series, we discussed intelligent document processing (IDP), and how IDP can accelerate claims processing use cases in the insurance industry. We discussed how we can use AWS AI services to accurately categorize claims documents along with supporting documents. Amazon Redshift is another service in the Analytics stack.

Analytics 75

Analytics APIs Healthcare Big data 75

AWS Machine Learning

JULY 7, 2022

Consider the following best practices when developing your bot: Manage bot schema via code – The Amazon Lex console provides an easy-to-use interface as you design and configure the bot, but relies on manual actions to replicate the setup. Identify user experience metrics – Defining the conversational experience can be hard.

Best practices 75

Best practices Metrics APIs Accountability 75

AWS Machine Learning

MAY 10, 2023

It provides a suite of tools for visualizing training metrics, examining model architectures, exploring embeddings, and more. When they create a SageMaker training job, domain users can use TensorBoard using the SageMaker Python SDK or Boto3 API. x_test / 255.0 x_test / 255.0 strftime("%d-%m-%Y-%H-%M-%S") region = boto3.session.Session().region_name

Scripts 73

Scripts Metrics Construction APIs 73

AWS Machine Learning

NOVEMBER 1, 2022

Although Autopilot eliminates the heavy lifting of building ML models, MLOps engineers still have to create, automate, and manage end-to-end ML workflows. In this post, we show how to create an end-to-end ML workflow to train and evaluate an Autopilot generated ML model using Pipelines and register it in the SageMaker model registry.

Scripts 78

Scripts APIs Metrics Engineering 78

AWS Machine Learning

JULY 6, 2023

SaaS platforms can integrate with SageMaker across the ML lifecycle from data labeling and preparation to model training, hosting, monitoring, and managing models with various components, as shown in the following figure. Creating such metadata can help SaaS providers manage the end-to-end lifecycle of the ML model more effectively.

SaaS 76

SaaS Accountability APIs Engineering 76

AWS Machine Learning

JANUARY 12, 2023

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 squad-level overrides are documented in GitHub on how to use them. Conclusion.

Engineering 111

Engineering APIs Accountability Metrics 111

AWS Machine Learning

OCTOBER 5, 2022

Beyond the financial impact, ATOs damage the customer experience, threaten brand loyalty and reputation, and strain fraud teams as they manage chargebacks and customer claims. This post discusses how to create a real-time detector endpoint using the new Account Takeover Insights (ATI) model in Amazon Fraud Detector. Upload event data.

Accountability 70

Accountability APIs Metrics Engineering 70

Totango

APRIL 26, 2021

Digital Engagement – Living in a digital world means timely digital tools to manage, visualize, and drive the digital journey. As part of the Digital Engagement focus, next week we will share more on how to manage your customers’ digital journey in Totango using SucceasBLOCs. In Kyoto, we’re investing in: .

Scripts 62

Scripts APIs Customer retention Enterprise 62

AWS Machine Learning

JULY 19, 2022

In this post, we show how to label, train, and build a computer vision model to detect rooftops and solar panels from satellite images. To test the model output, we use a Jupyter notebook to run Python code to detect custom labels in a supplied image by calling Amazon Rekognition APIs. Fine-tune the trained model.

APIs 70

APIs Metrics Enterprise Government 70

AWS Machine Learning

NOVEMBER 22, 2022

We also demonstrate how to understand the different sentiments associated with specific entities in the text (such as company, product, person, or brand) directly from the API. The Amazon Comprehend sentiment API identifies the overall sentiment for a text document. Use cases for real-time sentiment analysis.

APIs 68

APIs CRM Feedback B2C 68

AWS Machine Learning

MARCH 29, 2023

The Independent Evaluation Office (IEO) is a functionally independent office within the UNDP that supports the oversight and accountability functions of the Executive Board and management of the UNDP, UNCDF, and UNV. This API processes the documents and stores the JSON output files in Amazon S3 for postprocessing.

APIs 69

APIs Construction Metrics Technology 69

AWS Machine Learning

SEPTEMBER 8, 2023

The TextractAsync task calls Amazon Textract using the asynchronous Application Programming Interface (API) following best practices with Amazon Simple Notification Service ( Amazon SNS ) notifications and OutputConfig to store the Amazon Textract JSON output to a customer Amazon S3 bucket. The Map State processes each chunk in parallel.

Construction 107

Construction Metrics Best practices APIs 107

AWS Machine Learning

JULY 24, 2023

Patsnap provides a global one-stop platform for patent search, analysis, and management. In this section, we show how to build your own container, deploy your own GPT-2 model, and test with the SageMaker endpoint API. implement the model and the inference API. Specifically, Dockerfile and build.sh gpt2 and predictor.py

APIs 66

APIs Engineering Construction Benchmark 66

SharpenCX

MARCH 2, 2021

You can tailor your digital customer experience to different kinds of users these days, so it’s important to know how to reach each of your targeted demographics. Look at metrics to identify customer demographics and behaviors. Do my systems have APIs so our teams can build custom integrations if we need to?

Customer Experience 67

Customer Experience Coaching Call Center Contact Center 67

AWS Machine Learning

APRIL 6, 2023

Overall, Forecast outperformed all other methods based on a backtesting approach (described in the Evaluation Metrics section later in this post) for macro-level sales prediction. The Boto3 API provides the create_auto_predictor function for training an auto prediction model. We evaluated the model performance using the WAPE.

Sales 80

Sales Metrics APIs Marketing 80

AWS Machine Learning

DECEMBER 21, 2022

Amazon SageMaker Feature Store is a purpose-built feature management solution that helps data scientists and ML engineers securely store, discover, and share curated data used in training and prediction workflows. SageMaker Feature Store consists of an online and an offline mode for managing features.

Scripts 73

Scripts Engineering APIs Big data 73