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People (1 result)
Activities & events
| Title & Speakers | Event |
|---|---|
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Global AI EXPO
2025-12-10 · 18:00
Global AI Expo 2025 is a full-day, hands-on showcase of the biggest ideas in AI—built for people who learn by seeing and doing. Explore how AI is transforming industries, test emerging tools, and gain practical skills that prepare you for the future of work. You’ll roam across themed halls, join live demos and code-along workshops, network on your own terms, and—new this year—participate in a dedicated Global AI Job Fair in the final two hours. When : Date : Dec 10, 2025 Time : From 1 pm - 5 pm (Your local Time) Format: Virtual - https://events.tao.ai/pod/analytics.club/9kpr6q1mqod1/source--me What to Expect
The Halls
Who Should Attend
Why Join
If you have any questions, please email us at : [email protected] Tags AI jobs, #machine learning jobs, data science jobs, LLM engineer, MLOps engineer, AI recruiter, tech hiring, AI careers, ML internships, entry-level AI, senior AI roles, portfolio review, interview prep, resume tips, employer booths, remote AI roles, hiring fair, virtual job fair, career networking, talent matching, recruiters |
Global AI EXPO
|
|
Global AI EXPO
2025-12-10 · 18:00
Global AI Expo 2025 is a full-day, hands-on showcase of the biggest ideas in AI—built for people who learn by seeing and doing. Explore how AI is transforming industries, test emerging tools, and gain practical skills that prepare you for the future of work. You’ll roam across themed halls, join live demos and code-along workshops, network on your own terms, and—new this year—participate in a dedicated Global AI Job Fair in the final two hours. When : Date : Dec 10, 2025 Time : From 1 pm - 5 pm (Your local Time) Format: Virtual - https://events.tao.ai/pod/analytics.club/9kpr6q1mqod1/source--me What to Expect
The Halls
Who Should Attend
Why Join
If you have any questions, please email us at : [email protected] Tags AI jobs, #machine learning jobs, data science jobs, LLM engineer, MLOps engineer, AI recruiter, tech hiring, AI careers, ML internships, entry-level AI, senior AI roles, portfolio review, interview prep, resume tips, employer booths, remote AI roles, hiring fair, virtual job fair, career networking, talent matching, recruiters |
Global AI EXPO
|
|
Global AI EXPO
2025-12-10 · 13:00
Global AI Expo 2025 is a full-day, hands-on showcase of the biggest ideas in AI—built for people who learn by seeing and doing. Explore how AI is transforming industries, test emerging tools, and gain practical skills that prepare you for the future of work. You’ll roam across themed halls, join live demos and code-along workshops, network on your own terms, and—new this year—participate in a dedicated Global AI Job Fair in the final two hours. When : Date : Dec 10, 2025 Time : From 1 pm - 5 pm (Your local Time) Format: Virtual - https://events.tao.ai/pod/analytics.club/9kpr6q1mqod1/source--me What to Expect
The Halls
Who Should Attend
Why Join
If you have any questions, please email us at : [email protected] Tags AI jobs, #machine learning jobs, data science jobs, LLM engineer, MLOps engineer, AI recruiter, tech hiring, AI careers, ML internships, entry-level AI, senior AI roles, portfolio review, interview prep, resume tips, employer booths, remote AI roles, hiring fair, virtual job fair, career networking, talent matching, recruiters |
Global AI EXPO
|
|
Global AI EXPO
2025-12-10 · 12:00
Global AI Expo 2025 is a full-day, hands-on showcase of the biggest ideas in AI—built for people who learn by seeing and doing. Explore how AI is transforming industries, test emerging tools, and gain practical skills that prepare you for the future of work. You’ll roam across themed halls, join live demos and code-along workshops, network on your own terms, and—new this year—participate in a dedicated Global AI Job Fair in the final two hours. When : Date : Dec 10, 2025 Time : From 1 pm - 5 pm (Your local Time) Format: Virtual - https://events.tao.ai/pod/analytics.club/9kpr6q1mqod1/source--me What to Expect
The Halls
Who Should Attend
Why Join
If you have any questions, please email us at : [email protected] Tags AI jobs, #machine learning jobs, data science jobs, LLM engineer, MLOps engineer, AI recruiter, tech hiring, AI careers, ML internships, entry-level AI, senior AI roles, portfolio review, interview prep, resume tips, employer booths, remote AI roles, hiring fair, virtual job fair, career networking, talent matching, recruiters |
Global AI EXPO
|
|
Global AI EXPO
2025-12-10 · 12:00
Global AI Expo 2025 is a full-day, hands-on showcase of the biggest ideas in AI—built for people who learn by seeing and doing. Explore how AI is transforming industries, test emerging tools, and gain practical skills that prepare you for the future of work. You’ll roam across themed halls, join live demos and code-along workshops, network on your own terms, and—new this year—participate in a dedicated Global AI Job Fair in the final two hours. When : Date : Dec 10, 2025 Time : From 1 pm - 5 pm (Your local Time) Format: Virtual - https://events.tao.ai/pod/analytics.club/9kpr6q1mqod1/source--me What to Expect
The Halls
Who Should Attend
Why Join
If you have any questions, please email us at : [email protected] Tags AI jobs, #machine learning jobs, data science jobs, LLM engineer, MLOps engineer, AI recruiter, tech hiring, AI careers, ML internships, entry-level AI, senior AI roles, portfolio review, interview prep, resume tips, employer booths, remote AI roles, hiring fair, virtual job fair, career networking, talent matching, recruiters |
Global AI EXPO
|
|
Global AI EXPO
2025-12-10 · 12:00
Global AI Expo 2025 is a full-day, hands-on showcase of the biggest ideas in AI—built for people who learn by seeing and doing. Explore how AI is transforming industries, test emerging tools, and gain practical skills that prepare you for the future of work. You’ll roam across themed halls, join live demos and code-along workshops, network on your own terms, and—new this year—participate in a dedicated Global AI Job Fair in the final two hours. When : Date : Dec 10, 2025 Time : From 1 pm - 5 pm (Your local Time) Format: Virtual - https://events.tao.ai/pod/analytics.club/9kpr6q1mqod1/source--me What to Expect
The Halls
Who Should Attend
Why Join
If you have any questions, please email us at : [email protected] Tags AI jobs, #machine learning jobs, data science jobs, LLM engineer, MLOps engineer, AI recruiter, tech hiring, AI careers, ML internships, entry-level AI, senior AI roles, portfolio review, interview prep, resume tips, employer booths, remote AI roles, hiring fair, virtual job fair, career networking, talent matching, recruiters |
Global AI EXPO
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|
Oct 2 - Women in AI Virtual Event
2025-10-02 · 16:00
Hear talks from experts on the latest topics in AI, ML, and computer vision. Date and Time Oct 2 at 9 AM Pacific Location Virtual. Register for the Zoom. The Hidden Order of Intelligent Systems: Complexity, Autonomy, and the Future of AI As artificial intelligence systems grow more autonomous and integrated into our world, they also become harder to predict, control, and fully understand. This talk explores how complexity theory can help us make sense of these challenges, by revealing the hidden patterns that drive collective behavior, adaptation, and resilience in intelligent systems. From emergent coordination among autonomous agents to nonlinear feedback in real-world deployments, we’ll explore how order arises from chaos, and what that means for the next generation of AI. Along the way, we’ll draw connections to neuroscience, agentic AI, and distributed systems that offer fresh insights into designing multi-faceted AI systems. About the Speaker Ria Cheruvu is a Senior Trustworthy AI Architect at NVIDIA. She holds a master’s degree in data science from Harvard and teaches data science and ethical AI across global platforms. Ria is passionate about uncovering the hidden dynamics that shape intelligent systems—from natural networks to artificial ones. Managing Medical Imaging Datasets: From Curation to Evaluation High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment. We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities. Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact. About the Speaker Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. Building Agents That Learn: Managing Memory in AI Agents In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent's functionality. In this talk, we will explore these types of memory, discuss challenges with managing agentic memory, and present practical solutions for building agentic systems that can learn from their past executions and personalize their interactions over time. About the Speaker Apoorva Joshi is a Data Scientist turned Developer Advocate, with over 7 years of experience applying machine learning to problems in domains such as cybersecurity and mental health. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications through written content and hands-on workshops. Human-Centered AI: Soft Skills That Make Visual AI Work in Manufacturing Visual AI systems can spot defects and optimize workflows—but it’s people who train, deploy, and trust the results. This session explores the often-overlooked soft skills that make Visual AI implementations successful: communication, cross-functional collaboration, documentation habits, and on-the-floor leadership. Sheena Yap Chan shares practical strategies to reduce resistance to AI tools, improve adoption rates, and build inclusive teams where operators, engineers, and executives align. Attendees will leave with actionable techniques to drive smoother, people-first AI rollouts in manufacturing environments. About the Speaker Sheena Yap Chan is a Wall Street Journal Bestselling Author, leadership speaker and consultant who helps organizations develop confidence, communication, and collaboration skills that drive innovation and team performance—especially in high-tech, high-change industries. She’s worked with leaders across engineering, operations, and manufacturing to align people with digital transformation goals. |
Oct 2 - Women in AI Virtual Event
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|
Oct 2 - Women in AI Virtual Event
2025-10-02 · 16:00
Hear talks from experts on the latest topics in AI, ML, and computer vision. Date and Time Oct 2 at 9 AM Pacific Location Virtual. Register for the Zoom. The Hidden Order of Intelligent Systems: Complexity, Autonomy, and the Future of AI As artificial intelligence systems grow more autonomous and integrated into our world, they also become harder to predict, control, and fully understand. This talk explores how complexity theory can help us make sense of these challenges, by revealing the hidden patterns that drive collective behavior, adaptation, and resilience in intelligent systems. From emergent coordination among autonomous agents to nonlinear feedback in real-world deployments, we’ll explore how order arises from chaos, and what that means for the next generation of AI. Along the way, we’ll draw connections to neuroscience, agentic AI, and distributed systems that offer fresh insights into designing multi-faceted AI systems. About the Speaker Ria Cheruvu is a Senior Trustworthy AI Architect at NVIDIA. She holds a master’s degree in data science from Harvard and teaches data science and ethical AI across global platforms. Ria is passionate about uncovering the hidden dynamics that shape intelligent systems—from natural networks to artificial ones. Managing Medical Imaging Datasets: From Curation to Evaluation High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment. We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities. Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact. About the Speaker Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. Building Agents That Learn: Managing Memory in AI Agents In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent's functionality. In this talk, we will explore these types of memory, discuss challenges with managing agentic memory, and present practical solutions for building agentic systems that can learn from their past executions and personalize their interactions over time. About the Speaker Apoorva Joshi is a Data Scientist turned Developer Advocate, with over 7 years of experience applying machine learning to problems in domains such as cybersecurity and mental health. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications through written content and hands-on workshops. Human-Centered AI: Soft Skills That Make Visual AI Work in Manufacturing Visual AI systems can spot defects and optimize workflows—but it’s people who train, deploy, and trust the results. This session explores the often-overlooked soft skills that make Visual AI implementations successful: communication, cross-functional collaboration, documentation habits, and on-the-floor leadership. Sheena Yap Chan shares practical strategies to reduce resistance to AI tools, improve adoption rates, and build inclusive teams where operators, engineers, and executives align. Attendees will leave with actionable techniques to drive smoother, people-first AI rollouts in manufacturing environments. About the Speaker Sheena Yap Chan is a Wall Street Journal Bestselling Author, leadership speaker and consultant who helps organizations develop confidence, communication, and collaboration skills that drive innovation and team performance—especially in high-tech, high-change industries. She’s worked with leaders across engineering, operations, and manufacturing to align people with digital transformation goals. |
Oct 2 - Women in AI Virtual Event
|
|
Oct 2 - Women in AI Virtual Event
2025-10-02 · 16:00
Hear talks from experts on the latest topics in AI, ML, and computer vision. Date and Time Oct 2 at 9 AM Pacific Location Virtual. Register for the Zoom. The Hidden Order of Intelligent Systems: Complexity, Autonomy, and the Future of AI As artificial intelligence systems grow more autonomous and integrated into our world, they also become harder to predict, control, and fully understand. This talk explores how complexity theory can help us make sense of these challenges, by revealing the hidden patterns that drive collective behavior, adaptation, and resilience in intelligent systems. From emergent coordination among autonomous agents to nonlinear feedback in real-world deployments, we’ll explore how order arises from chaos, and what that means for the next generation of AI. Along the way, we’ll draw connections to neuroscience, agentic AI, and distributed systems that offer fresh insights into designing multi-faceted AI systems. About the Speaker Ria Cheruvu is a Senior Trustworthy AI Architect at NVIDIA. She holds a master’s degree in data science from Harvard and teaches data science and ethical AI across global platforms. Ria is passionate about uncovering the hidden dynamics that shape intelligent systems—from natural networks to artificial ones. Managing Medical Imaging Datasets: From Curation to Evaluation High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment. We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities. Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact. About the Speaker Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. Building Agents That Learn: Managing Memory in AI Agents In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent's functionality. In this talk, we will explore these types of memory, discuss challenges with managing agentic memory, and present practical solutions for building agentic systems that can learn from their past executions and personalize their interactions over time. About the Speaker Apoorva Joshi is a Data Scientist turned Developer Advocate, with over 7 years of experience applying machine learning to problems in domains such as cybersecurity and mental health. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications through written content and hands-on workshops. Human-Centered AI: Soft Skills That Make Visual AI Work in Manufacturing Visual AI systems can spot defects and optimize workflows—but it’s people who train, deploy, and trust the results. This session explores the often-overlooked soft skills that make Visual AI implementations successful: communication, cross-functional collaboration, documentation habits, and on-the-floor leadership. Sheena Yap Chan shares practical strategies to reduce resistance to AI tools, improve adoption rates, and build inclusive teams where operators, engineers, and executives align. Attendees will leave with actionable techniques to drive smoother, people-first AI rollouts in manufacturing environments. About the Speaker Sheena Yap Chan is a Wall Street Journal Bestselling Author, leadership speaker and consultant who helps organizations develop confidence, communication, and collaboration skills that drive innovation and team performance—especially in high-tech, high-change industries. She’s worked with leaders across engineering, operations, and manufacturing to align people with digital transformation goals. |
Oct 2 - Women in AI Virtual Event
|
|
Oct 2 - Women in AI Virtual Event
2025-10-02 · 16:00
Hear talks from experts on the latest topics in AI, ML, and computer vision. Date and Time Oct 2 at 9 AM Pacific Location Virtual. Register for the Zoom. The Hidden Order of Intelligent Systems: Complexity, Autonomy, and the Future of AI As artificial intelligence systems grow more autonomous and integrated into our world, they also become harder to predict, control, and fully understand. This talk explores how complexity theory can help us make sense of these challenges, by revealing the hidden patterns that drive collective behavior, adaptation, and resilience in intelligent systems. From emergent coordination among autonomous agents to nonlinear feedback in real-world deployments, we’ll explore how order arises from chaos, and what that means for the next generation of AI. Along the way, we’ll draw connections to neuroscience, agentic AI, and distributed systems that offer fresh insights into designing multi-faceted AI systems. About the Speaker Ria Cheruvu is a Senior Trustworthy AI Architect at NVIDIA. She holds a master’s degree in data science from Harvard and teaches data science and ethical AI across global platforms. Ria is passionate about uncovering the hidden dynamics that shape intelligent systems—from natural networks to artificial ones. Managing Medical Imaging Datasets: From Curation to Evaluation High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment. We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities. Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact. About the Speaker Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. Building Agents That Learn: Managing Memory in AI Agents In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent's functionality. In this talk, we will explore these types of memory, discuss challenges with managing agentic memory, and present practical solutions for building agentic systems that can learn from their past executions and personalize their interactions over time. About the Speaker Apoorva Joshi is a Data Scientist turned Developer Advocate, with over 7 years of experience applying machine learning to problems in domains such as cybersecurity and mental health. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications through written content and hands-on workshops. Human-Centered AI: Soft Skills That Make Visual AI Work in Manufacturing Visual AI systems can spot defects and optimize workflows—but it’s people who train, deploy, and trust the results. This session explores the often-overlooked soft skills that make Visual AI implementations successful: communication, cross-functional collaboration, documentation habits, and on-the-floor leadership. Sheena Yap Chan shares practical strategies to reduce resistance to AI tools, improve adoption rates, and build inclusive teams where operators, engineers, and executives align. Attendees will leave with actionable techniques to drive smoother, people-first AI rollouts in manufacturing environments. About the Speaker Sheena Yap Chan is a Wall Street Journal Bestselling Author, leadership speaker and consultant who helps organizations develop confidence, communication, and collaboration skills that drive innovation and team performance—especially in high-tech, high-change industries. She’s worked with leaders across engineering, operations, and manufacturing to align people with digital transformation goals. |
Oct 2 - Women in AI Virtual Event
|
|
Oct 2 - Women in AI Virtual Event
2025-10-02 · 16:00
Hear talks from experts on the latest topics in AI, ML, and computer vision. Date and Time Oct 2 at 9 AM Pacific Location Virtual. Register for the Zoom. The Hidden Order of Intelligent Systems: Complexity, Autonomy, and the Future of AI As artificial intelligence systems grow more autonomous and integrated into our world, they also become harder to predict, control, and fully understand. This talk explores how complexity theory can help us make sense of these challenges, by revealing the hidden patterns that drive collective behavior, adaptation, and resilience in intelligent systems. From emergent coordination among autonomous agents to nonlinear feedback in real-world deployments, we’ll explore how order arises from chaos, and what that means for the next generation of AI. Along the way, we’ll draw connections to neuroscience, agentic AI, and distributed systems that offer fresh insights into designing multi-faceted AI systems. About the Speaker Ria Cheruvu is a Senior Trustworthy AI Architect at NVIDIA. She holds a master’s degree in data science from Harvard and teaches data science and ethical AI across global platforms. Ria is passionate about uncovering the hidden dynamics that shape intelligent systems—from natural networks to artificial ones. Managing Medical Imaging Datasets: From Curation to Evaluation High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment. We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities. Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact. About the Speaker Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. Building Agents That Learn: Managing Memory in AI Agents In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent's functionality. In this talk, we will explore these types of memory, discuss challenges with managing agentic memory, and present practical solutions for building agentic systems that can learn from their past executions and personalize their interactions over time. About the Speaker Apoorva Joshi is a Data Scientist turned Developer Advocate, with over 7 years of experience applying machine learning to problems in domains such as cybersecurity and mental health. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications through written content and hands-on workshops. Human-Centered AI: Soft Skills That Make Visual AI Work in Manufacturing Visual AI systems can spot defects and optimize workflows—but it’s people who train, deploy, and trust the results. This session explores the often-overlooked soft skills that make Visual AI implementations successful: communication, cross-functional collaboration, documentation habits, and on-the-floor leadership. Sheena Yap Chan shares practical strategies to reduce resistance to AI tools, improve adoption rates, and build inclusive teams where operators, engineers, and executives align. Attendees will leave with actionable techniques to drive smoother, people-first AI rollouts in manufacturing environments. About the Speaker Sheena Yap Chan is a Wall Street Journal Bestselling Author, leadership speaker and consultant who helps organizations develop confidence, communication, and collaboration skills that drive innovation and team performance—especially in high-tech, high-change industries. She’s worked with leaders across engineering, operations, and manufacturing to align people with digital transformation goals. |
Oct 2 - Women in AI Virtual Event
|
|
Oct 2 - Women in AI Virtual Event
2025-10-02 · 16:00
Hear talks from experts on the latest topics in AI, ML, and computer vision. Date and Time Oct 2 at 9 AM Pacific Location Virtual. Register for the Zoom. The Hidden Order of Intelligent Systems: Complexity, Autonomy, and the Future of AI As artificial intelligence systems grow more autonomous and integrated into our world, they also become harder to predict, control, and fully understand. This talk explores how complexity theory can help us make sense of these challenges, by revealing the hidden patterns that drive collective behavior, adaptation, and resilience in intelligent systems. From emergent coordination among autonomous agents to nonlinear feedback in real-world deployments, we’ll explore how order arises from chaos, and what that means for the next generation of AI. Along the way, we’ll draw connections to neuroscience, agentic AI, and distributed systems that offer fresh insights into designing multi-faceted AI systems. About the Speaker Ria Cheruvu is a Senior Trustworthy AI Architect at NVIDIA. She holds a master’s degree in data science from Harvard and teaches data science and ethical AI across global platforms. Ria is passionate about uncovering the hidden dynamics that shape intelligent systems—from natural networks to artificial ones. Managing Medical Imaging Datasets: From Curation to Evaluation High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment. We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities. Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact. About the Speaker Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. Building Agents That Learn: Managing Memory in AI Agents In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent's functionality. In this talk, we will explore these types of memory, discuss challenges with managing agentic memory, and present practical solutions for building agentic systems that can learn from their past executions and personalize their interactions over time. About the Speaker Apoorva Joshi is a Data Scientist turned Developer Advocate, with over 7 years of experience applying machine learning to problems in domains such as cybersecurity and mental health. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications through written content and hands-on workshops. Human-Centered AI: Soft Skills That Make Visual AI Work in Manufacturing Visual AI systems can spot defects and optimize workflows—but it’s people who train, deploy, and trust the results. This session explores the often-overlooked soft skills that make Visual AI implementations successful: communication, cross-functional collaboration, documentation habits, and on-the-floor leadership. Sheena Yap Chan shares practical strategies to reduce resistance to AI tools, improve adoption rates, and build inclusive teams where operators, engineers, and executives align. Attendees will leave with actionable techniques to drive smoother, people-first AI rollouts in manufacturing environments. About the Speaker Sheena Yap Chan is a Wall Street Journal Bestselling Author, leadership speaker and consultant who helps organizations develop confidence, communication, and collaboration skills that drive innovation and team performance—especially in high-tech, high-change industries. She’s worked with leaders across engineering, operations, and manufacturing to align people with digital transformation goals. |
Oct 2 - Women in AI Virtual Event
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|
Oct 2 - Women in AI Virtual Event
2025-10-02 · 16:00
Hear talks from experts on the latest topics in AI, ML, and computer vision. Date and Time Oct 2 at 9 AM Pacific Location Virtual. Register for the Zoom. The Hidden Order of Intelligent Systems: Complexity, Autonomy, and the Future of AI As artificial intelligence systems grow more autonomous and integrated into our world, they also become harder to predict, control, and fully understand. This talk explores how complexity theory can help us make sense of these challenges, by revealing the hidden patterns that drive collective behavior, adaptation, and resilience in intelligent systems. From emergent coordination among autonomous agents to nonlinear feedback in real-world deployments, we’ll explore how order arises from chaos, and what that means for the next generation of AI. Along the way, we’ll draw connections to neuroscience, agentic AI, and distributed systems that offer fresh insights into designing multi-faceted AI systems. About the Speaker Ria Cheruvu is a Senior Trustworthy AI Architect at NVIDIA. She holds a master’s degree in data science from Harvard and teaches data science and ethical AI across global platforms. Ria is passionate about uncovering the hidden dynamics that shape intelligent systems—from natural networks to artificial ones. Managing Medical Imaging Datasets: From Curation to Evaluation High-quality data is the cornerstone of effective machine learning in healthcare. This talk presents practical strategies and emerging techniques for managing medical imaging datasets, from synthetic data generation and curation to evaluation and deployment. We’ll begin by highlighting real-world case studies from leading researchers and practitioners who are reshaping medical imaging workflows through data-centric practices. The session will then transition into a hands-on tutorial using FiftyOne, the open-source platform for visual dataset inspection and model evaluation. Attendees will learn how to load, visualize, curate, and evaluate medical datasets across various imaging modalities. Whether you're a researcher, clinician, or ML engineer, this talk will equip you with practical tools and insights to improve dataset quality, model reliability, and clinical impact. About the Speaker Paula Ramos has a PhD in Computer Vision and Machine Learning, with more than 20 years of experience in the technological field. She has been developing novel integrated engineering technologies, mainly in Computer Vision, robotics, and Machine Learning applied to agriculture, since the early 2000s in Colombia. Building Agents That Learn: Managing Memory in AI Agents In the rapidly evolving landscape of agentic systems, memory management has emerged as a key pillar for building intelligent, context-aware AI Agents. Different types of memory, such as short-term and long-term memory, play distinct roles in supporting an agent's functionality. In this talk, we will explore these types of memory, discuss challenges with managing agentic memory, and present practical solutions for building agentic systems that can learn from their past executions and personalize their interactions over time. About the Speaker Apoorva Joshi is a Data Scientist turned Developer Advocate, with over 7 years of experience applying machine learning to problems in domains such as cybersecurity and mental health. As an AI Developer Advocate at MongoDB, she now helps developers be successful at building AI applications through written content and hands-on workshops. Human-Centered AI: Soft Skills That Make Visual AI Work in Manufacturing Visual AI systems can spot defects and optimize workflows—but it’s people who train, deploy, and trust the results. This session explores the often-overlooked soft skills that make Visual AI implementations successful: communication, cross-functional collaboration, documentation habits, and on-the-floor leadership. Sheena Yap Chan shares practical strategies to reduce resistance to AI tools, improve adoption rates, and build inclusive teams where operators, engineers, and executives align. Attendees will leave with actionable techniques to drive smoother, people-first AI rollouts in manufacturing environments. About the Speaker Sheena Yap Chan is a Wall Street Journal Bestselling Author, leadership speaker and consultant who helps organizations develop confidence, communication, and collaboration skills that drive innovation and team performance—especially in high-tech, high-change industries. She’s worked with leaders across engineering, operations, and manufacturing to align people with digital transformation goals. |
Oct 2 - Women in AI Virtual Event
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Practical Applications of Emerging Tech in Data Science
2024-09-26 · 12:00
Join us at PyData Turkiye on September 26th for a full day of exploration into the fascinating world of data science and AI. This conference unites data professionals and enthusiasts alike to share knowledge and uncover new possibilities. PyData Turkiye provides an excellent opportunity to network, gain insights, and discuss challenges and innovations in the field. Whether you're a seasoned data scientist or simply interested in the power of data, this event is tailored just for you. Join us for an inspiring day of learning and connection! Keynote Speaker:
Sessions:
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Practical Applications of Emerging Tech in Data Science
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To access this webinar, please register here: https://hubs.ly/Q02w8FjS0 Topic: "Accelerating End-to-End Financial Processing and Reporting with Pre-Trained and Custom ML Models" Speaker: Pablo Vega-Behar, AI / ML Product Owner & Tech Lead at The Fitch Group Pablo is a data science leader with over ten years of work experience and a passion for applying machine learning and natural language processing to solve real-world problems. He wants to leverage data and analytics to deliver insights, solutions, and value for businesses and customers. Pablo has a PhD in structural engineering, a fellowship in data science, and multiple certifications in AWS, Python, and machine learning. Abstract: Speed and accuracy of processing and reporting are paramount in the financial services industry, yet the sector has been slow to fully embrace emerging technologies, such as artificial intelligence, to significantly enhance these processes. Our talk introduces an innovative approach to overcoming these obstacles. At Fitch Group, we leverage the strengths of pre-trained and custom-developed Machine Learning (ML) models. We're developing this end-to-end system to navigate the complexities of financial data and content generation for financial customers effectively. This talk will discuss our component-based approach that is already delivering business value as we progress towards our long-term goal of establishing an end-to-end processing and content generation pipeline. I will highlight areas where we opted to develop custom ML models, such as processing fundamental financials from reports and tables, and where we've integrated pre-trained LLMs to enhance content generation and expedite analyst research. Attendees will be introduced to practical applications and case studies demonstrating how our hybrid intelligence approach has significantly enhanced our workflows. This method has streamlined the sourcing, extraction, and analysis of financial data, improved our efficiency in generating comprehensive reports and insights, and will broaden the spectrum of financial insights we can offer. This session is designed to equip financial professionals, data scientists, and technologists with the insights needed to adopt similar strategies, enabling them to streamline their own financial processes and reporting capabilities to align with the demands of contemporary finance. ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02zdcSk0 • Code of conduct: https://odsc.com/code-of-conduct/ |
Acc End-to-End Financial Processing& Reporting with Pre-Trained&Custom ML Models
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To access this webinar, please register here: https://hubs.ly/Q02w8FjS0 Topic: "Accelerating End-to-End Financial Processing and Reporting with Pre-Trained and Custom ML Models" Speaker: Pablo Vega-Behar, AI / ML Product Owner & Tech Lead at The Fitch Group Pablo is a data science leader with over ten years of work experience and a passion for applying machine learning and natural language processing to solve real-world problems. He wants to leverage data and analytics to deliver insights, solutions, and value for businesses and customers. Pablo has a PhD in structural engineering, a fellowship in data science, and multiple certifications in AWS, Python, and machine learning. Abstract: Speed and accuracy of processing and reporting are paramount in the financial services industry, yet the sector has been slow to fully embrace emerging technologies, such as artificial intelligence, to significantly enhance these processes. Our talk introduces an innovative approach to overcoming these obstacles. At Fitch Group, we leverage the strengths of pre-trained and custom-developed Machine Learning (ML) models. We're developing this end-to-end system to navigate the complexities of financial data and content generation for financial customers effectively. This talk will discuss our component-based approach that is already delivering business value as we progress towards our long-term goal of establishing an end-to-end processing and content generation pipeline. I will highlight areas where we opted to develop custom ML models, such as processing fundamental financials from reports and tables, and where we've integrated pre-trained LLMs to enhance content generation and expedite analyst research. Attendees will be introduced to practical applications and case studies demonstrating how our hybrid intelligence approach has significantly enhanced our workflows. This method has streamlined the sourcing, extraction, and analysis of financial data, improved our efficiency in generating comprehensive reports and insights, and will broaden the spectrum of financial insights we can offer. This session is designed to equip financial professionals, data scientists, and technologists with the insights needed to adopt similar strategies, enabling them to streamline their own financial processes and reporting capabilities to align with the demands of contemporary finance. ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02zdcSk0 • Code of conduct: https://odsc.com/code-of-conduct/ |
Acc End-to-End Financial Processing& Reporting with Pre-Trained&Custom ML Models
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To access this webinar, please register here: https://hubs.ly/Q02w8FjS0 Topic: "Accelerating End-to-End Financial Processing and Reporting with Pre-Trained and Custom ML Models" Speaker: Pablo Vega-Behar, AI / ML Product Owner & Tech Lead at The Fitch Group Pablo is a data science leader with over ten years of work experience and a passion for applying machine learning and natural language processing to solve real-world problems. He wants to leverage data and analytics to deliver insights, solutions, and value for businesses and customers. Pablo has a PhD in structural engineering, a fellowship in data science, and multiple certifications in AWS, Python, and machine learning. Abstract: Speed and accuracy of processing and reporting are paramount in the financial services industry, yet the sector has been slow to fully embrace emerging technologies, such as artificial intelligence, to significantly enhance these processes. Our talk introduces an innovative approach to overcoming these obstacles. At Fitch Group, we leverage the strengths of pre-trained and custom-developed Machine Learning (ML) models. We're developing this end-to-end system to navigate the complexities of financial data and content generation for financial customers effectively. This talk will discuss our component-based approach that is already delivering business value as we progress towards our long-term goal of establishing an end-to-end processing and content generation pipeline. I will highlight areas where we opted to develop custom ML models, such as processing fundamental financials from reports and tables, and where we've integrated pre-trained LLMs to enhance content generation and expedite analyst research. Attendees will be introduced to practical applications and case studies demonstrating how our hybrid intelligence approach has significantly enhanced our workflows. This method has streamlined the sourcing, extraction, and analysis of financial data, improved our efficiency in generating comprehensive reports and insights, and will broaden the spectrum of financial insights we can offer. This session is designed to equip financial professionals, data scientists, and technologists with the insights needed to adopt similar strategies, enabling them to streamline their own financial processes and reporting capabilities to align with the demands of contemporary finance. ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02zdcSk0 • Code of conduct: https://odsc.com/code-of-conduct/ |
Acc End-to-End Financial Processing& Reporting with Pre-Trained&Custom ML Models
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To access this webinar, please register here: https://hubs.ly/Q02w8FjS0 Topic: "Accelerating End-to-End Financial Processing and Reporting with Pre-Trained and Custom ML Models" Speaker: Pablo Vega-Behar, AI / ML Product Owner & Tech Lead at The Fitch Group Pablo is a data science leader with over ten years of work experience and a passion for applying machine learning and natural language processing to solve real-world problems. He wants to leverage data and analytics to deliver insights, solutions, and value for businesses and customers. Pablo has a PhD in structural engineering, a fellowship in data science, and multiple certifications in AWS, Python, and machine learning. Abstract: Speed and accuracy of processing and reporting are paramount in the financial services industry, yet the sector has been slow to fully embrace emerging technologies, such as artificial intelligence, to significantly enhance these processes. Our talk introduces an innovative approach to overcoming these obstacles. At Fitch Group, we leverage the strengths of pre-trained and custom-developed Machine Learning (ML) models. We're developing this end-to-end system to navigate the complexities of financial data and content generation for financial customers effectively. This talk will discuss our component-based approach that is already delivering business value as we progress towards our long-term goal of establishing an end-to-end processing and content generation pipeline. I will highlight areas where we opted to develop custom ML models, such as processing fundamental financials from reports and tables, and where we've integrated pre-trained LLMs to enhance content generation and expedite analyst research. Attendees will be introduced to practical applications and case studies demonstrating how our hybrid intelligence approach has significantly enhanced our workflows. This method has streamlined the sourcing, extraction, and analysis of financial data, improved our efficiency in generating comprehensive reports and insights, and will broaden the spectrum of financial insights we can offer. This session is designed to equip financial professionals, data scientists, and technologists with the insights needed to adopt similar strategies, enabling them to streamline their own financial processes and reporting capabilities to align with the demands of contemporary finance. ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02zdcSk0 • Code of conduct: https://odsc.com/code-of-conduct/ |
Acc End-to-End Financial Processing& Reporting with Pre-Trained&Custom ML Models
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To access this webinar, please register here: https://hubs.ly/Q02w8FjS0 Topic: "Accelerating End-to-End Financial Processing and Reporting with Pre-Trained and Custom ML Models" Speaker: Pablo Vega-Behar, AI / ML Product Owner & Tech Lead at The Fitch Group Pablo is a data science leader with over ten years of work experience and a passion for applying machine learning and natural language processing to solve real-world problems. He wants to leverage data and analytics to deliver insights, solutions, and value for businesses and customers. Pablo has a PhD in structural engineering, a fellowship in data science, and multiple certifications in AWS, Python, and machine learning. Abstract: Speed and accuracy of processing and reporting are paramount in the financial services industry, yet the sector has been slow to fully embrace emerging technologies, such as artificial intelligence, to significantly enhance these processes. Our talk introduces an innovative approach to overcoming these obstacles. At Fitch Group, we leverage the strengths of pre-trained and custom-developed Machine Learning (ML) models. We're developing this end-to-end system to navigate the complexities of financial data and content generation for financial customers effectively. This talk will discuss our component-based approach that is already delivering business value as we progress towards our long-term goal of establishing an end-to-end processing and content generation pipeline. I will highlight areas where we opted to develop custom ML models, such as processing fundamental financials from reports and tables, and where we've integrated pre-trained LLMs to enhance content generation and expedite analyst research. Attendees will be introduced to practical applications and case studies demonstrating how our hybrid intelligence approach has significantly enhanced our workflows. This method has streamlined the sourcing, extraction, and analysis of financial data, improved our efficiency in generating comprehensive reports and insights, and will broaden the spectrum of financial insights we can offer. This session is designed to equip financial professionals, data scientists, and technologists with the insights needed to adopt similar strategies, enabling them to streamline their own financial processes and reporting capabilities to align with the demands of contemporary finance. ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02zdcSk0 • Code of conduct: https://odsc.com/code-of-conduct/ |
Acc End-to-End Financial Processing& Reporting with Pre-Trained&Custom ML Models
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|
To access this webinar, please register here: https://hubs.ly/Q02w8FjS0 Topic: "Accelerating End-to-End Financial Processing and Reporting with Pre-Trained and Custom ML Models" Speaker: Pablo Vega-Behar, AI / ML Product Owner & Tech Lead at The Fitch Group Pablo is a data science leader with over ten years of work experience and a passion for applying machine learning and natural language processing to solve real-world problems. He wants to leverage data and analytics to deliver insights, solutions, and value for businesses and customers. Pablo has a PhD in structural engineering, a fellowship in data science, and multiple certifications in AWS, Python, and machine learning. Abstract: Speed and accuracy of processing and reporting are paramount in the financial services industry, yet the sector has been slow to fully embrace emerging technologies, such as artificial intelligence, to significantly enhance these processes. Our talk introduces an innovative approach to overcoming these obstacles. At Fitch Group, we leverage the strengths of pre-trained and custom-developed Machine Learning (ML) models. We're developing this end-to-end system to navigate the complexities of financial data and content generation for financial customers effectively. This talk will discuss our component-based approach that is already delivering business value as we progress towards our long-term goal of establishing an end-to-end processing and content generation pipeline. I will highlight areas where we opted to develop custom ML models, such as processing fundamental financials from reports and tables, and where we've integrated pre-trained LLMs to enhance content generation and expedite analyst research. Attendees will be introduced to practical applications and case studies demonstrating how our hybrid intelligence approach has significantly enhanced our workflows. This method has streamlined the sourcing, extraction, and analysis of financial data, improved our efficiency in generating comprehensive reports and insights, and will broaden the spectrum of financial insights we can offer. This session is designed to equip financial professionals, data scientists, and technologists with the insights needed to adopt similar strategies, enabling them to streamline their own financial processes and reporting capabilities to align with the demands of contemporary finance. ODSC Links: • Get free access to more talks/trainings like this at Ai+ Training platform: https://hubs.li/H0Zycsf0 • ODSC blog: https://opendatascience.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/_ODSC & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: https://hubs.li/Q02zdcSk0 • Code of conduct: https://odsc.com/code-of-conduct/ |
Acc End-to-End Financial Processing& Reporting with Pre-Trained&Custom ML Models
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