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X-WR-CALDESC:Events for Arize AI
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DTSTART;VALUE=DATE:20221101
DTEND;VALUE=DATE:20221104
DTSTAMP:20260513T032153
CREATED:20220623T193151Z
LAST-MODIFIED:20220825T165052Z
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SUMMARY:ODSC West
DESCRIPTION:
URL:https://arize.com/community-events/odsc-west-2/
LOCATION:Hyatt Regency San Francisco Airport\, United States
ATTACH;FMTTYPE=image/webp:https://arize.com/wp-content/uploads/2022/08/odsc.webp
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221102T090000
DTEND;TZID=America/Los_Angeles:20221102T093000
DTSTAMP:20260513T032153
CREATED:20221020T150851Z
LAST-MODIFIED:20221103T201355Z
UID:10000326-1667379600-1667381400@arize.com
SUMMARY:Pragmatic Applications Series: Improving Churn Models
DESCRIPTION:You are a machine learning engineer at a credit card company who is responsible for building a model to predict customer churn. After building your model\, you will need to monitor its performance\, drift\, as well as any data quality issues in production. Arize will show you how to monitor and troubleshoot performance\, drift and data quality issues in production. \nIn this workshop\, you’ll learn best practices for how to: \n\nSet-up performance\, drift and data quality monitoring to better understand how your model is performing. \nDiscover feature drifts corresponding to time periods of performance degradation and how to resolve them.\nCheck to see if explainability and algorithm bias are having an impact on your model decisions. 
URL:https://arize.com/community-events/pragmatic-applications-series-improving-churn-models/
LOCATION:Virtual\, United States
ATTACH;FMTTYPE=image/jpeg:https://arize.com/wp-content/uploads/2022/10/Pragmatic-Applications-Series-Churn.jpg
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DTSTART;TZID=America/Los_Angeles:20221109T090000
DTEND;TZID=America/Los_Angeles:20221109T093000
DTSTAMP:20260513T032153
CREATED:20221020T151101Z
LAST-MODIFIED:20221103T200932Z
UID:10000327-1667984400-1667986200@arize.com
SUMMARY:Pragmatic Applications: Detecting Fraud
DESCRIPTION:Every year\, fraud costs the global economy over $5 trillion. AI practitioners are on the front lines of this battle building and deploying sophisticated ML models to detect fraud\, saving organizations billions of dollars in the process. Of course\, it’s a challenging task as fraud takes many forms and attacks vectors across industries. ML teams need an approach that is both reactive in monitoring key metrics and proactive in measuring drift\, counter-abuse ML teams. \nIn this webinar\, you’ll learn best practices for how to: \n\nAccount for model\, feature and actuals drift to ensure your models stay relevant\nTroubleshoot performance degradations across various cohorts\nAvoid common pitfalls from misleading evaluation metrics to imbalanced datasets
URL:https://arize.com/community-events/pragmatic-applications-detecting-fraud/
LOCATION:Virtual\, United States
ATTACH;FMTTYPE=image/jpeg:https://arize.com/wp-content/uploads/2022/10/Pragmatic-Applications-Series-Fraud.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221116T090000
DTEND;TZID=America/Los_Angeles:20221116T093000
DTSTAMP:20260513T032153
CREATED:20221020T151215Z
LAST-MODIFIED:20221103T163304Z
UID:10000328-1668589200-1668591000@arize.com
SUMMARY:Pragmatic Applications: NLP Classification
DESCRIPTION:From images and video to natural language and audio\, unstructured data coupled with machine learning can unlock deeper AI potential and ROI for many organizations and use cases. Embeddings are the core of how deep learning models represent structures and are fundamental to how the next generation of ML models work. \nJoin this workshop to: \n\nTroubleshoot a sentiment classification model in production\nLearn about emerging techniques like UMAP to transform unstructured data into embeddings that can be more efficiently processed by ML models\nImplement new technologies to monitor and improve models in production\n\nSign up now and try out these approaches and tools in a hands-on workshop!
URL:https://arize.com/community-events/pragmatic-applications-nlp-classification/
LOCATION:Virtual\, United States
ATTACH;FMTTYPE=image/jpeg:https://arize.com/wp-content/uploads/2022/10/Pragmatic-Applications-Series-NLP.jpg
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20221128
DTEND;VALUE=DATE:20221201
DTSTAMP:20260513T032153
CREATED:20220423T212628Z
LAST-MODIFIED:20221116T191410Z
UID:10000376-1669593600-1669852799@arize.com
SUMMARY:Toronto Machine Learning Summit 2022
DESCRIPTION:
URL:https://arize.com/community-events/toronto-machine-learning-summit-2022/
LOCATION:Toronto\, Canada\, Toronto\, Canada
ATTACH;FMTTYPE=image/png:https://arize.com/wp-content/uploads/2022/08/TMLS-Logo.png
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20221130T080000
DTEND;TZID=America/Los_Angeles:20221130T170000
DTSTAMP:20260513T032153
CREATED:20221020T151300Z
LAST-MODIFIED:20221103T163128Z
UID:10000329-1669795200-1669827600@arize.com
SUMMARY:Pragmatic Applications: - Optimize Demand Forecasting
DESCRIPTION:
URL:https://arize.com/community-events/pragmatic-applications-optimize-demand-forecasting/
LOCATION:Virtual\, United States
ATTACH;FMTTYPE=image/jpeg:https://arize.com/wp-content/uploads/2022/10/Pragmatic-Applications-Series-Demand-Forecasting.jpg
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