AWS Machine Learning

MAY 18, 2023

Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. Choose Data sources in the navigation pane. You can now also choose OAuth 2.0

Groups 76

Groups Knowledge Base Policies Examples 76

AWS Machine Learning

AUGUST 14, 2023

This blog post is co-written with Tuana Çelik from deepset. However, we need to ensure that the LLMs limit the responses to company data, thereby mitigating model hallucinations. Some of the models offer capabilities for you to fine-tune them with your own data.

Knowledge Base 69

Knowledge Base Examples Data Analytics 69

AWS Machine Learning

APRIL 11, 2023

Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science. As a data scientist, you may want to showcase your findings for a dataset, or deploy a trained model. The code for this blog can be found in this GitHub repository.

Resources 73

Resources Automotive System Sports 73

AWS Machine Learning

AUGUST 30, 2023

This template includes sample data containing AWS online documentation for Amazon Kendra, Amazon Lex, and SageMaker. Deploying the stack requires about 30 minutes followed by about 15 minutes to synchronize it and ingest the data in the index. Review your options from the qnabot-on-aws-plugin-samples repository README.

Self Service 104

Self Service Contact Center Multi-Channel Knowledge Base 104

AWS Machine Learning

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

Connections 106

Connections Analysis Resources Analytics 106

Team Support

JUNE 20, 2023

In this blog, we will explore the five best practices that customer support teams should implement to provide great customer experiences even in challenging times. By creating a repository of pre-approved, well-crafted responses, agents can quickly address customer concerns without reinventing the wheel each time.

Self Service 97

Self Service Chatbots Analytics Knowledge Base 97

AWS Machine Learning

DECEMBER 20, 2022

The IMDb and Box Office Mojo Movies/TV/OTT licensable data package provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million movie, TV, and entertainment titles; and global box office reporting data from more than 60 countries.

Entertainment 83

Entertainment Data Video Resources 83

AWS Machine Learning

MAY 17, 2023

Most importantly, none of your data is used to train the underlying models. Because all data is encrypted and doesn’t leave the virtual private cloud (VPC), you can trust that your data will remain private and confidential. For additional posts on ML at AWS, visit the AWS ML Blog. format(' '.join(chunk_summaries),

Meeting 70

Meeting Training Video How To 70

AWS Machine Learning

SEPTEMBER 22, 2023

To improve the base model’s instruction-following ability, human data annotators are tasked with authoring responses to various prompts. The collected responses (often referred to as demonstration data) are used in a process called supervised fine-tuning (SFT). The following diagram illustrates this architecture. yaml sft_hh.py

Training 99

Training Policies e-support Data 99

AWS Machine Learning

OCTOBER 26, 2023

Amazon Kendra helps you easily aggregate content from a variety of content repositories into a centralized index that lets you quickly search all your enterprise data and find the most accurate answer. For more information, see Overview of access management: Permissions and policies and IAM roles for Drupal data sources.

Policies 98

Policies Data Groups Software 98

AWS Machine Learning

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production.

Healthcare 90

Healthcare Government Innovation Training 90

AWS Machine Learning

AUGUST 16, 2023

This is a guest blog post co-written with Ben Veasey, Jeremy Anderson, Jordan Knight, and June Li from Travelers. Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. We build on the code provided in the DINO repository.

Training 72

Training Multi-Channel Travel Innovation 72

Optimove

OCTOBER 26, 2023

Why it matters: Without the harmonious operation of a Customer Data Platform (CDP) and a Multichannel Marketing Hub (MMH), B2C marketers looking to employ Customer-Led Marketing strategies risk alienating customers with mistimed, irrelevant, and impersonal messages. This fragmentation leads to inconsistent and disjointed customer experience.

Customer Experience 69

Customer Experience B2C Social Media Touchpoint 69

ChurnZero

JUNE 14, 2022

This is a guest blog contributed by Stephanie Neale, CEO of Blind Zebra , a sales and client success training company for B2B pros. If you haven’t already, pull as much historical churn data as possible. Create a repository to capture at-risk indicators as they pop up. It’s a Tuesday morning. It’s from one of your top accounts.

Strategy 98

Strategy B2B Meeting Customer Success 98

AWS Machine Learning

DECEMBER 22, 2023

Highly accurate LLMs can require terabytes of training data and thousands or even millions of hours of accelerator compute time to achieve target accuracy. PyTorch offers Fully Sharded Data Parallelism (FSDP) as its main method for supporting large training workload across many compute devices. To mitigate this problem, SMP v2.0

Training 100

Training User Experience Communication Data 100

Clarivate

MARCH 6, 2024

We leverage the Derwent World Patents Index (DWPI ), which acts as a repository of human invention and patented problem solving, curated by Clarivate expert editors. The Top 100 Global Innovators methodology uses a complete comparative analysis of global inventions data to assess the strength of every patented idea.

Innovation 52

Innovation Report Analysis Analytics 52

AWS Machine Learning

MARCH 6, 2024

Various cancers Data source: Urquhart, L. In the following sections, we go through the steps to prepare your training data, create a training script, and run a SageMaker training job. We could resample our data and discard records from the majority class. COVID-19 Spikevax Moderna $21.8 COVID-19 Humira AbbVie $21.6

Training 94

Training Examples Data How To 94

AWS Machine Learning

OCTOBER 26, 2023

This increase in data input significantly improves the accuracy of product detection within our models, further boosting the overall efficacy of our shopping systems. This Python function implements data parallelism at the module level on models created by the PyTorch Neuron API. Cost savings : We slashed inference costs.

Retail 101

Retail Innovation System Video 101

AWS Machine Learning

AUGUST 22, 2022

With Amazon Kendra, you can easily aggregate content from a variety of content repositories into a centralized index that lets you quickly search all your enterprise data and find the most accurate answer. For more information, see Overview of access management: Permissions and policies and IAM roles for Alfresco data sources.

Policies 71

Policies Data Travel Management 71

AWS Machine Learning

JANUARY 5, 2024

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems.

Data 112

Data Management Effort Score Training 112

AWS Machine Learning

APRIL 19, 2023

Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts. After reading a few blog posts and DJL’s official documentation, we were sure DJL would provide the best solution to our problem. Solution overview The following diagram compares the previous and updated architecture.

Sports 75

Sports Training Effort Score Multi-Channel 75

AWS Machine Learning

SEPTEMBER 28, 2023

Data is ingested into the platform as a bulk upload on day 0 and then incremental uploads day 1+. ​ The generated response is provided back to the user via the web platform. Data source We created an Amazon Kendra index and added a data source using web crawler connectors with a root web URL and directory depth of two levels.

Knowledge Base 98

Knowledge Base Chatbots Self Service System 98

Totango

JUNE 1, 2021

Being able to use your customer success data will enable you to better connect with your customers. The reality of the unique relationship you share with your customers is captured in the data your customer success software gathers, detailing usage rates, demographics, logged interactions, voice of customer data, and other key metrics.

Customer Insights 69

Customer Insights Software How To Touchpoint 69

AWS Machine Learning

NOVEMBER 2, 2022

IDP helps transform structured, semi-structured, and unstructured data from a variety of document formats into actionable information. Processing unstructured data has become much easier with the advancements in optical character recognition (OCR), machine learning (ML), and natural language processing (NLP). billion in 2022.

Data 72

Data Resources Government System 72

AWS Machine Learning

FEBRUARY 14, 2023

It indexes the documents stored in a wide range of repositories and finds the most relevant document based on the keywords or natural language questions the user has searched for. In this blog post, we focus on retrieving custom search results that apply to a specific user or user group.

Chatbots 80

Chatbots How To Course Groups 80

AWS Machine Learning

DECEMBER 19, 2022

This blog post demonstrates how to perform ML inference using an object detection model from the PyTorch Model Zoo within SageMaker. Setting up these ML models as a SageMaker endpoint or SageMaker Batch Transform job for online or offline inference is easy with the steps outlined in this blog post. Solution overview. Step 1: Setup.

Effort Score 75

Effort Score Automotive Sports Training 75

AWS Machine Learning

AUGUST 21, 2023

To run it yourself, clone the GitHub repository and open the Jupyter notebook file. Solution overview SageMaker Clarify provides ML developers with purpose-built tools to gain greater insights into their ML training data and models. The notebook and code from this post are available on GitHub.

Hospitality 77

Hospitality Healthcare Training Report 77

ChurnZero

JUNE 14, 2022

This is a guest blog contributed by Stephanie Neale, CEO of Blind Zebra , a sales and client success training company for B2B pros. If you haven’t already, pull as much historical churn data as possible. Create a repository to capture at-risk indicators as they pop up. It’s a Tuesday morning. It’s from one of your top accounts.

Strategy 52

Strategy B2B Meeting Customer Success 52

AWS Machine Learning

JUNE 30, 2022

To deploy the solution using AWS SAM, you can find the latest code in the aws-security GitHub repository , where you can also contribute to the sample code. Clone the repository at [link]. The following commands show how to deploy the solution using the AWS SAM CLI. If not currently installed, install the AWS SAM CLI.

Policies 81

Policies Resources Connections Consulting 81

AWS Machine Learning

OCTOBER 2, 2023

Solution overview In Part 1 of this series, we laid out an architecture for our end-to-end MLOps pipeline that automates the entire machine learning (ML) process, from data labeling to model training and deployment at the edge. Make inference calls against the loaded model with the prepared image data.

Training 91

Training Software System Effort Score 91

AWS Machine Learning

MAY 25, 2023

Furthermore, FMs are trained with a point in time snapshot of data and have no inherent ability to access fresh data at inference time; without this ability they might provide responses that are potentially incorrect or inadequate. Amazon SageMaker Processing jobs for large scale data ingestion into OpenSearch.

Chatbots 77

Chatbots Data Training How To 77

AWS Machine Learning

MAY 19, 2023

In this blog post we walk you through the Solution Architecture behind “Describe For Me”, and the design considerations of our solution. Image Caption Hugging Face is an open-source community and data science platform that allows users to share, build, train, and deploy machine learning models. I recognize one person: Kanbo.

Video 90

Video Training Conference Technology 90

Circular Edge

NOVEMBER 9, 2020

PS – Check out CE’s InFocus Recap Blog for More Highlights including 9.2 Resubmit failed jobs with the originally used criteria (Data selection, PO values, etc.). – User Spec Repository Tables in Central Objects Datasource in place of local specs on FAT client for development. local Oracle Database).

Self Service 52

Self Service Resources System Tools 52

AWS Machine Learning

JULY 20, 2022

As new data privacy regulations like GDPR (General Data Protection Regulation, 2017) have come into effect, customers are under increased pressure to monetize media assets while abiding by the new rules. You can access the solution’s code repository for a detailed view of how we implement its components. AWS Media Intelligence.

Advertising 80

Advertising Automotive Industry How To 80

AWS Machine Learning

SEPTEMBER 9, 2022

However, as a new product in a new space for Amazon, Amp needed more relevant data to inform their decision-making process. Part 1 shows how data was collected and processed using the data and analytics platform, and Part 2 shows how the data was used to create show recommendations using Amazon SageMaker , a fully managed ML service.

Analytics 69

Analytics Data Customer Engagement Engagement 69

AWS Machine Learning

JULY 29, 2022

This is the second part of a series that showcases the machine learning (ML) lifecycle with a data mesh design pattern for a large enterprise with multiple lines of business (LOBs) and a Center of Excellence (CoE) for analytics and ML. In this post, we address the analytics and ML platform team as a consumer in the data mesh.

Training 71

Training Data Analytics Consumers 71

Upstream Works

FEBRUARY 26, 2020

With these new technologies, we have a far greater range of touchpoints for collecting data about customers. There are numerous repositories of customer data that feed into the contact center’s collective understanding of customers.

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Contact Center Self Service Omni-Channel Social Media 78