Difference between revisions of "Best Practices"

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• Cloud-enhanced ML
 
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• Featured use case demo: hospital readmission prediction (addresses running in InterSystems IRIS of the models trained outside the platform's control)  
 
• Featured use case demo: hospital readmission prediction (addresses running in InterSystems IRIS of the models trained outside the platform's control)  
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<b>Conversational AI: Best Practices for Building Bots
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</b><br>Conversational digital affordances are fast becoming a norm for users everywhere – from the office to the kitchen; from the car to the living room. We can type, tap or talk to all manner of device, apps, bots and agents to do all manner of things. When designed well, conversational AI experiences are natural, intuitive and efficient. In this session, we’ll provide practical guidance for building great bots. We’ll put the guidance to work using the Bot Builder v4 SDK, bot development tools and [[Microsoft]] Cognitive Services.
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<youtube>66TgH0YV4eA</youtube>
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<b>Visualization Best Practices for Explainable AI
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</b><br>How do you know if a machine learning model is trustworthy or potentially biased? One of the top trends in analytics is the rise of explainable AI, the practice of presenting transparent views into how algorithms make decisions. In this session, we will dive deeper into understanding and explaining machine learning terms and charts to the business using Tableau. We will walk through real-world examples from healthcare, retail, marketing, banking, and other industries.
 
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Revision as of 20:09, 9 September 2020

YouTube search... ...Google search

Rules of ML
Google research scientist Martin Zinkevich

Best Practices of In-Platform AI/ML Webinar
Productive use of machine learning and artificial intelligence technologies is impossible without a platform that allows autonomous functioning of AI/ML mechanisms. In-platform AI/ML has a number of advantages that can be obtained via best practices by InterSystems. On this webinar, we will present: • MLOps as the natural paradigm for in-platform AI/ML • A full cycle of AI/ML content development and in-platform deployment (including bidirectional integration of Jupyter with InterSystems IRIS) • New toolset added to ML Toolkit: integration and orchestration for Julia mathematical modeling environment • Automated AI/ML model selection and parameter determination via an SQL query • Cloud-enhanced ML • Featured use case demo: hospital readmission prediction (addresses running in InterSystems IRIS of the models trained outside the platform's control)

Conversational AI: Best Practices for Building Bots
Conversational digital affordances are fast becoming a norm for users everywhere – from the office to the kitchen; from the car to the living room. We can type, tap or talk to all manner of device, apps, bots and agents to do all manner of things. When designed well, conversational AI experiences are natural, intuitive and efficient. In this session, we’ll provide practical guidance for building great bots. We’ll put the guidance to work using the Bot Builder v4 SDK, bot development tools and Microsoft Cognitive Services.

Visualization Best Practices for Explainable AI
How do you know if a machine learning model is trustworthy or potentially biased? One of the top trends in analytics is the rise of explainable AI, the practice of presenting transparent views into how algorithms make decisions. In this session, we will dive deeper into understanding and explaining machine learning terms and charts to the business using Tableau. We will walk through real-world examples from healthcare, retail, marketing, banking, and other industries.