AWS Machine Learning

NOVEMBER 17, 2022

For DataEngineerPwd and DataScientistPwd , enter your own password for the data engineer and data scientist users. For S3BucketNameForInput , enter blog-studio-pii-dataset-. For S3BucketNameForOutput , enter blog-studio-output-. For Tags , add the key userprofilename and the value data-engineer. Choose Next.

Engineering 63

Engineering Big data Accountability Analytics 63

AWS Machine Learning

FEBRUARY 13, 2024

SageMaker provides end-to-end ML development, deployment, and monitoring capabilities such as a SageMaker Studio notebook environment for writing code, data acquisition, data tagging, model training, model tuning, deployment, monitoring, and much more.

Engineering 98

Engineering Gamification Scripts Big data 98

AWS Machine Learning

AUGUST 26, 2022

Refer to notebook examples for SageMaker algorithms – SageMaker provides a suite of built-in algorithms to help data scientists and ML practitioners get started with training and deploying ML models quickly. It tags (classifies) each pixel of the input image with a class label from a predefined set of classes. Semantic segmentation.

APIs 78

APIs Scripts Enterprise Big data 78

Peter Lavers

NOVEMBER 26, 2015

In my new line of work, I get to speak at industry conferences, read data/analytics/research publications and scan the plethora of blogs or social media comments on this topic. Ever since Google made “ data scientist ” the sexy job title for the decade, both suppliers and users have obsessed with technology and technical skills.

CRM 100

CRM Analytics Consulting Consulting 100

AWS Machine Learning

JULY 29, 2022

You manage data and resource access for each role and not at an individual user level. attributes, tags on Studio user profiles, and tags on SageMaker execution roles. GetAtt SageMakerDomain.Outputs.SageMakerDomainId SessionExpiration: 43200 Tags: - Key: Team Value: Team1 UserSettings: ExecutionRole: !GetAtt

Management 73

Management APIs Accountability Construction 73

Nicereply

MAY 28, 2020

This is the reason why you can’t just take a set of conversations tagged by your agents and throw them to a machine learning algorithm. Make sure to avoid noise as much as possible when building your training data. In general, the more training data you have, the better. No matter how good the algorithm is, it will fail.

Customer Support 92

Customer Support APIs Big data Personalization 92

ProProfs Blog

DECEMBER 11, 2020

This blog lists 6 impressive strategies that will help you measure your service quality and take your services from ‘mediocre’ to ‘exceptional’. One has to monitor and consider indirect mentions and casual tags as well. Measuring your service quality can be the first necessary step any business can take in improving their services.

Metrics 78

Metrics Customer Service Surveys Customer effort 78