Top Tweets for #mlexplainability
Dropout isn't just magicโit's math.
๐ Master the Law of Total Probability โ https://t.co/XwpnuQZwDP
#MathematicsOfML #Dropout #Probability #100DaysChallenge #MLExplainability

Also, #trust and #MLexplainability is a huge element where #UX can help -- think about how you surface recommendations and how you design to explain it!

Check out my latest blog post overviewing Model Explainability!
Learn about global, cohort, and local model explainability and how you can use explainability in your ML workflow!
https://t.co/9HRdbZRhKU
#MLExplainability #xAI #MLObservability #ModelObservability

We're growing! A warm welcome to Andy Lu, Harrison Chu, Krystal Kirkland, David Monical, Eric Senzig, and Francisco Castillo Carrasco for joining the Arize AI team!
#MLObservability #MLMonitoring #MLExplainability #xAI #AIML
(p.s. we're hiring!)
https://t.co/BuTwelt0OU
Prepare data for predicting credit risk using Amazon SageMaker Data Wrangler and Amazon SageMaker Clarify via @AWSCloud #AI #MachineLearning #CreditRisk #MLExplainability
https://t.co/71qDgewHPq
This week's recap: a big win! Arize AI was listed in Forbes Most Promising AI Companies of 2021 list. We couldn't have done it without our awesome team.
#MLObservability #MLMonitoring #MlOps #MLExplainability #xAI
https://t.co/RITR1KoaWr

Our ML Ecosystem101 Whitepaper is out now! We simplify the different stages involved in the ML workflow and bring clarity to the daunting ML Infrastructure space. Gone are the days of utter confusion!
Read more:
https://t.co/YC4xQVt7US
#MLObservability #MLOps #MLExplainability

My latest post on Forbes is live! https://t.co/77wAvWb0y1
Find out why business executives should understand the core of ML tooling and the 3 tools that can make your business successful in the age of AI/ML!
#MLMonitoring #MLObservability #MLExplainability #MLOps #xAI
We're thrilled to introduce Tammy Le (@tams_37) as our Vice President of Marketing & Strategy! Check out our latest and greatest here:
https://t.co/td9OTm7Qy7
#MLObservability #MLMonitoring #MLExplainability #MLOps
#MLexplainability does more than just explain model outcomes. It improves #MLquality and #AItrustworthiness throughout the lifecycle. This means more deployments and more opportunities captured.
Read the latest in the series.
https://t.co/SePOXoPCwL
#XAI #trustworthyAI

Flowers are blooming and Arize AI is growing! Three cheers for Kunal Shah!
#MLObservability #MLMonitoring #MLExplainability #MLOps
https://t.co/tmGtMeR8G5
How Zopa enhanced their fraud detection application using Amazon SageMaker Clarify via @AWSCloud #AI #MachineLearning #MLExplainability #MLBiasCorrection #FraudDetection https://t.co/sE6TJsgJrd
Using @Algorithmia? Hereโs a tool you can use to monitor AI performance and fairness. Introducing complete #MLMonitoring for your #Algorithmia deployments. To learn more, click here: https://t.co/ucpFuklIou #MLObservability #MLExplainability #MLOps

We're thrilled to be recognized as one of the industries most impactful companies in insideBIGDATA'S IMPACT 50 list for Q1 2021! @insideBigData
#MLMonitoring #MLObservability #MLExplainability
https://t.co/57Ld9bKzVV
How Clarify helps machine learning developers detect unintended bias via @amazonscience #AI #MachineLearning #MLExplainability https://t.co/xZXbdeqlNi

Amazon SageMaker Clarify Detects Bias and Increases the Transparency of Machine Learning Models via @AWSCloud #AI #MachineLearning #MLExplainability https://t.co/JvsV4yCmgR

Time to start thinking about #mlexplainability. The Risks of AutoML and How to Avoid Them. https://t.co/Ig7BrrLS3y #hbr #automl #bias
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