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Fine-tune and deploy a summarizer model using the Hugging Face Amazon SageMaker containers bringing your own script

AWS Machine Learning

Build your training script for the Hugging Face SageMaker estimator. script to use with Script Mode and pass hyperparameters for training. Thanks to our custom inference script hosted in a SageMaker endpoint, we can generate several summaries for this review with different text generation parameters. If we use an ml.g4dn.16xlarge

Scripts 104
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11 Contact Center Technologies to Boost Customer Satisfaction

TechSee

Recognizing that continuously adding quality agents simply does not add up financially, more and more companies are turning to technology in order to scale quality support. Founded in 2015, TechSee is a technology and technical support company that specializes in visual technology and augmented reality. ” 2. Coveo.

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

AWS Machine Learning

We create a custom training container that downloads data directly from the Snowflake table into the training instance rather than first downloading the data into an S3 bucket. 1 with the following additions: The Snowflake Connector for Python to download the data from the Snowflake table to the training instance.

Scripts 136
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Automate Amazon SageMaker Pipelines DAG creation

AWS Machine Learning

You can then iterate on preprocessing, training, and evaluation scripts, as well as configuration choices. framework/createmodel/ – This directory contains a Python script that creates a SageMaker model object based on model artifacts from a SageMaker Pipelines training step. script is used by pipeline_service.py The model_unit.py

Scripts 129
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How Twilio used Amazon SageMaker MLOps pipelines with PrestoDB to enable frequent model retraining and optimized batch transform

AWS Machine Learning

Batch transform The batch transform pipeline consists of the following steps: The pipeline implements a data preparation step that retrieves data from a PrestoDB instance (using a data preprocessing script ) and stores the batch data in Amazon Simple Storage Service (Amazon S3).

Scripts 130
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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

Run the script init-script.bash : chmod u+x init-script.bash./init-script.bash init-script.bash This script prompts you for the following: The Amazon Bedrock knowledge base ID to associate with your Google Chat app (refer to the prerequisites section). The script deploys the AWS CDK project in your account.

APIs 131
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21 Business Analysts & Call Center Leaders Reveal the Optimal Role of the Business Analyst in Call Center Operations

Callminer

Business analysts must stay up to date on the latest call center technologies and solutions that can optimize, automate and modernize call center operations. They serve as a bridge between IT and other business functions, making data-driven recommendations that meet business requirements and improve processes while optimizing costs.