Remove account-management-training
article thumbnail

Efficient continual pre-training LLMs for financial domains

AWS Machine Learning

Large language models (LLMs) are generally trained on large publicly available datasets that are domain agnostic. For example, Meta’s Llama models are trained on datasets such as CommonCrawl , C4 , Wikipedia, and ArXiv. The resulting LLM outperforms LLMs trained on non-domain-specific datasets when tested on finance-specific tasks.

article thumbnail

Unlocking the Power of Healthcare Contact Centers: Enhancing Patient Care in the Digital Age

InMoment XI

At its core, a healthcare contact center is a centralized hub equipped with trained personnel and technology to manage inbound and outbound communications related to healthcare services.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Announcing Rekogniton Custom Moderation: Enhance accuracy of pre-trained Rekognition moderation models with your data

AWS Machine Learning

Many companies currently depend on human moderators or respond reactively to user complaints to manage inappropriate user-generated content. In this post, we discuss how to use the Custom Moderation feature in Amazon Rekognition to enhance the accuracy of your pre-trained content moderation API.

Training 108
article thumbnail

Sales Training Metrics That Matter

Integrity Solutions

While investing in sales training can produce a range of benefits, all of us in sales know it all boils down to the bottom line. Here are the sales training metrics you should be using to measure your success. How to Determine Sales Training Metrics. There are a number of factors contributing to this dismal return rate.

article thumbnail

6 Killer Applications for Artificial Intelligence in the Customer Engagement Contact Center

If Artificial Intelligence for businesses is a red-hot topic in C-suites, AI for customer engagement and contact center customer service is white hot. This white paper covers specific areas in this domain that offer potential for transformational ROI, and a fast, zero-risk way to innovate with AI.

article thumbnail

Train and deploy ML models in a multicloud environment using Amazon SageMaker

AWS Machine Learning

As customers accelerate their migrations to the cloud and transform their business, some find themselves in situations where they have to manage IT operations in a multicloud environment. We show how you can build and train an ML model in AWS and deploy the model in another platform.

Training 100
article thumbnail

Use Snowflake as a data source to train ML models with Amazon SageMaker

AWS Machine Learning

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. We add this data to Snowflake as a new table.

Training 105