Learn how to debug an AI model using the Responsible AI dashboard in Azure Machine Learning studio to ensure it performs responsibly and is less harmful. Create a responsible AI dashboard. Identify where the model has errors. Discover data over or under representation to mitigate biases. Understand what drives a model outcome with explainable and interpretability. Mitigate issues to meet compliance regulation requirements.

Learning objectives - Create a responsible AI dashboard. - Identify where the model has errors. - Discover data over or under representation to mitigate biases. - Understand what drives a model outcome with explainable and interpretability. - Mitigate issues to meet compliance regulation requirements.

Presenters: Nitya Narasimhan \|\| Senior Cloud Advocate - Microsoft - LinkedIn: https://www.linkedin.com/in/nityan/ Ruth Yakubu \|\| Cloud Advocate - Microsoft - Twitter: https://twitter.com/ruthieyakubu - LinkedIn: https://www.linkedin.com/in/ruthyakubu/

Moderators: Cynthia Zanoni \|\| Cloud Advocate - Microsoft - LinkedIn: https://www.linkedin.com/in/cynthiazanoni/

📌Full series information

📌More info here

Learn how to debug an AI model using the Responsible AI dashboard in Azure Machine Learning studio to ensure it performs responsibly and is less harmful. Create a responsible AI dashboard. Identify where the model has errors. Discover data over or under representation to mitigate biases. Understand what drives a model outcome with explainable and interpretability. Mitigate issues to meet compliance regulation requirements.

Learning objectives - Create a responsible AI dashboard. - Identify where the model has errors. - Discover data over or under representation to mitigate biases. - Understand what drives a model outcome with explainable and interpretability. - Mitigate issues to meet compliance regulation requirements.

Presenters: Nitya Narasimhan \|\| Senior Cloud Advocate - Microsoft - LinkedIn: https://www.linkedin.com/in/nityan/ Ruth Yakubu \|\| Cloud Advocate - Microsoft - Twitter: https://twitter.com/ruthieyakubu - LinkedIn: https://www.linkedin.com/in/ruthyakubu/

Moderators: Cynthia Zanoni \|\| Cloud Advocate - Microsoft - LinkedIn: https://www.linkedin.com/in/cynthiazanoni/

📌Full series information

📌More info here

** Important RSVP here (Due to room capacity and building security, you must pre-register at the link for admission)

Description: Welcome to our in-person AI meetup in New York. Join us for deep dive tech talks on AI, GenAI, LLMs and ML, hands-on workshops, food/drink, networking with speakers and fellow developers.

Tech Talk: End-to-End Development of Generative AI applications on Azure Speaker: Nitya Narasimhan (Microsoft) Abstract: In this talk we’ll introduce the core concepts for building a “copilot” application on Azure AI from prompt engineering to LLM Ops – using the Contoso Chat application sample as a reference. And we’ll explore the Azure AI Studio (preview) platform from a code-first perspective to understand how you can streamline your development from model exploration to endpoint deployment, with a unified platform and workflow.

Tech Talk: Train & Debug your ML Models For Responsible AI on Azure Speaker: Ruth Yakubu (Microsoft) Abstract: In this talk you will learn to train an AI model using the Azure Machine Learning Studio, then use its built-in Responsible AI Dashboard capability to debug your model for performance, fairness and responsible AI usage.

Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors: We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsor. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 20,000+ AI developers in New York or 300K+ worldwide.

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Hands-on workshop focusing on using Responsible AI tools to identify and mitigate issues that can negatively affect individuals or society. Participants will learn how to debug and mitigate ML model issues using error analysis, data analysis, model explainability, model performance and fairness assessment. Uses LLMs and traditional ML models. Prerequisites: Basic understanding of Python.

Responsible AI is a critical part of machine learning. With the recent breakthroughs in AI, there is increasing societal scrutiny for AI to be regulated. However, organizations and AI developers need practical tools to enable them to safe-guard, debug, mitigate and deliver AI solutions that are less harmful. This workshop provides hands-on learning to the AI communities on how they can use Responsible AI tools identity and mitigate issues that can negatively affect individual or society. Participants will learn using LLMs and traditional ML models to gain a competitive advantage with this workshop.

How do you think that a Start-up will be benefited from this session? This will help startups in reducing the risks from their AI services when engaging with investors, b2b customers deals, or end-users to win their trust. Investors and customers want to avoid regulatory AI compliance violations when evaluating AI systems from startups.

The session will focus on - The lessons from this workshop series will focus on debugging traditional ML models to expose blind spots that model performance metrics miss such as biases, interpretability, and pinpointing groups where a model is producing wrong results.

What will the attendees or a Start-up learn from session? Participants will learn how to debug and mitigate a ML model issue using error analysis, data analysis, model explainability, model performance and fairness assessment.

Read More - https://aka.ms/Responsible-AIPrinciples

Speaker Bio: Ruth Yakubu Ruth Yakubu is a Principal Cloud Advocate at Microsoft. Ruth specializes in Java, Advanced Analytics, Data Platforms and Artificial Intelligence (AI). In addition, she's been a tech speaker at several conferences like Microsoft Ignite, O'reilly velocity, Devoxx UK, Grace Hopper Dublin, TechSummit, Websummit and numerous other developer conferences. Prior to Microsoft, She has also worked for great companies like UNISYS, ACCENTURE and DIRECTV over the years where she gained a lot of experience with software architectural design and programming. She’s awarded Dzone.com’s Most Valued Blogger.

Social Handle of the speaker X-@ruthieyakubu LinkedIn- https://www.linkedin.com/in/ruthyakubu

Session hosted by- Vinayak Hegde Vinayak Hegde currently works as CTO-in-residence at Microsoft for Startups helping startups to scale their tech stacks, teams and products. With over 20 years of experience, Vinayak has built multiple products across different domains such as IoT, large scale networks and large-scale data systems in a variety of individual contributor and senior technical leadership roles. Previously he has worked with Akamai, Inmobi, and Zoomcar.

Social Handle LinkedIn- https://www.linkedin.com/in/vinayakh/

Pre-requisites: Basic understanding of Python

ReactorBengaluru

Pre-requisites: Basic understanding of Python is recommended.

Hands-on learning on building and evaluating generative AI solutions with LLMs responsibly at scale. Learn to create visual executable flows linking LLMs, vector embeddings, prompts, and Python tools; evaluate performance metrics and responsible AI issues such as groundedness, hallucinations, and relevance. Pre-requisites: Basic understanding of Python.

Responsible AI is a critical part of machine learning. With the recent breakthroughs in AI, there is increasing societal scrutiny for AI to be regulated. However, organizations and AI developers need practical tools to enable them to safe-guard, debug, mitigate and deliver AI solutions that are less harmful. This workshop provides hands-on learning to the AI communities on how they can use Responsible AI tools identity and mitigate issues that can negatively affect individual or society. Participants will learn using LLMs and traditional ML models to gain a competitive advantage with this workshop.

How do you think that a Start-up will be benefited from this session? This will help startups in reducing the risks from their AI services when engaging with investors, b2b customers deals, or end-users to win their trust. Investors and customers want to avoid regulatory AI compliance violations when evaluating AI systems from startups.

The session will focus on - The lessons from this workshop series will focus on building and evaluating generative AI solutions with LLMs responsibly at a large-scale.

What will the attendees or a Start-up learn from session? Participants will learn how to create visual executable flows that link LLMs, vector embeddings, prompts, and Python tools. As well as, evaluating performance metrics and responsible AI issues such as grounded ness, hallucinations, relevance etc.

Read More - https://aka.ms/Responsible-AIPrinciples

Speaker Bio: Ruth Yakubu Ruth Yakubu is a Principal Cloud Advocate at Microsoft. Ruth specializes in Java, Advanced Analytics, Data Platforms and Artificial Intelligence (AI). In addition, she's been a tech speaker at several conferences like Microsoft Ignite, O'reilly velocity, Devoxx UK, Grace Hopper Dublin, TechSummit, Websummit and numerous other developer conferences. Prior to Microsoft, She has also worked for great companies like UNISYS, ACCENTURE and DIRECTV over the years where she gained a lot of experience with software architectural design and programming. She’s awarded Dzone.com’s Most Valued Blogger.

Social Handle of the speaker X-@ruthieyakubu LinkedIn- https://www.linkedin.com/in/ruthyakubu

Session hosted by- Vinayak Hegde Vinayak Hegde currently works as CTO-in-residence at Microsoft for Startups helping startups to scale their tech stacks, teams and products. With over 20 years of experience, Vinayak has built multiple products across different domains such as IoT, large scale networks and large-scale data systems in a variety of individual contributor and senior technical leadership roles. Previously he has worked with Akamai, Inmobi, and Zoomcar.

Social Handle LinkedIn- https://www.linkedin.com/in/vinayakh/

Pre-requisites: Basic understanding of Python

ReactorBengaluru

Pre-requisites: Basic understanding of Python is recommended.

Learn how to improve search results and return more relevant results using semantic search and vector search in Azure Cognitive Search. This LIVE session is presented by two experts, and our moderators will answer your questions directly in the chat.

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * David Glover * Ruth Yakubu * Tim Fish * DE Producer 9 * Laurent Bugnion

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This video is one of many sessions delivered for the Microsoft Ignite 2023 event. View sessions on-demand and learn more about Microsoft Ignite at https://ignite.microsoft.com

BRK401LL | English (US) | AI & Apps

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