AWS Machine Learning

APRIL 21, 2023

This step uses the built-in ProcessingStep with the provided code, evaluation.py , to evaluate performance metrics (accuracy, area under curve). Configure the baseline step To monitor the model and data, a baseline is required. Monitoring for data drift requires a baseline of training data. medium', 'ml.m5.xlarge'],

Metrics 75

Metrics Telecommunications Analytics Healthcare 75

AWS Machine Learning

NOVEMBER 9, 2023

She holds a master’s degree in Computer Science specialized in Data Science from the University of Colorado, Boulder. Data Lake Architect with AWS Professional Services. She is passionate about solving customer pain points processing big data and providing long-term scalable solutions. Sunita Koppar is a Sr.

Scripts 102

Scripts Accountability Engineering Best practices 102

AWS Machine Learning

JANUARY 26, 2024

This is backed by our deep set of over 300 cloud security tools and the trust of our millions of customers, including the most security-sensitive organizations like government, healthcare, and financial services. Ram Vittal is a Principal ML Solutions Architect at AWS.

Best practices 124

Best practices Government Engineering Accountability 124

Callminer

NOVEMBER 6, 2019

Big data is getting bigger with each passing year, but making sense of trends hidden deep in the heap of 1s and 0s is more confounding than ever. As metrics pile up, you may find yourself wondering which data points matter and in what ways they relate to your business’s interests.

Big data 140

Big data Analytics Metrics Sales 140

AWS Machine Learning

JANUARY 30, 2023

Distributed training is a technique that allows for the parallel processing of large amounts of data across multiple machines or devices. By splitting the data and training multiple models in parallel, distributed training can significantly reduce training time and improve the performance of models on big data.

Benchmark 83

Benchmark Construction Metrics Big data 83

aircall

MAY 17, 2021

Companies rely heavily on reporting without the advantage of data and analytics that are so critical to establishing efficient, productive workflows. In today’s marketplace, automation, digitization, and big data are your friends. Healthcare occupations will likely rise due to a renewed focus on health and well-being.

Transportation 71

Transportation Entertainment voip Construction 71

AWS Machine Learning

SEPTEMBER 9, 2022

For logging, we utilize FluentD to push all our container logs to Amazon OpenSearch Service and system metrics to Prometheus. We then use Kibana and the Grafana UI for searching and filtering logs and metrics. Logging and monitoring. The following diagram describes how we set this up. Kubeflow Logging.

Engineering 77

Engineering Healthcare APIs Scripts 77

Stratifyd

JANUARY 29, 2019

Leverage marketing automation tools to develop and analyze key marketing metrics. Analyze and monitor data from marketing campaigns to gather user information, create user segmentation, and drive insights on ROI of marketing activities. Experience in AI, Big Data, Ecosystems, customer experience, and/or text analytics.

Marketing 40

Marketing Analytics Healthcare Big data 40

Stratifyd

DECEMBER 12, 2018

Leverage marketing automation tools to develop and analyze key marketing metrics. Proven ability to develop meaningful growth metrics. Experience and interest in AI and Big Data. Develop and manage the marketing strategy for all marketing channels. Create Pardot Drip campaigns and relevant campaign lists. Stratifyd, Inc.

Marketing 40

Marketing Management Analytics Healthcare 40

Stratifyd

DECEMBER 12, 2018

Leverage marketing automation tools to develop and analyze key marketing metrics. Proven ability to develop meaningful growth metrics. Experience and interest in AI and Big Data. Develop and manage the marketing strategy for all marketing channels. Strong analytical, critical thinking, and problem-solving skills.

Marketing 40

Marketing Management Analytics Healthcare 40