Rejoignez Marie SACKSICK - Data Scientist en cyber securité et Co-organisatrice à Paris Women in Machine Learning &amp; Data Science.

À l'occasion de la journée internationale des droits des femmes, notre podcast invite une data scientist team lead spécialisée dans la cyber sécurité pour discuter de la place des femmes dans l'intelligence artificielle.

✅ Dans une première partie du podcast, nous découvrirons le parcours inspirant de notre invitée.

✅ Ensuite, nous explorerons ensemble les défis et opportunités pour les femmes dans le domaine de l'IA, ainsi que les implications éthiques de l'utilisation de l'IA dans la société.

🎙️ Joignez-vous à nous pour une conversation inspirante et informative sur un sujet crucial pour l'avenir de la technologie.  

👉 Si comme Marie tu souhaites travailler sur des projets aussi passionnants, rends toi sur www.datarockstars.ai.

🚀 Invitée : Marie SACKSICK,

  Data Scientist Team Lead Chez CybelAngel
  Co-organisatrice WiMlDS (Paris Women in Machine Learning &amp; Data Science) 


Data Stories Inside - Episode #2 : Women in AI

Today, we are excited to have the esteemed Prof. Marcelo Guerra Hahn join us. 

Prof. Marcelo is a distinguished guest faculty member at the UW Information School at the University of Washington, Seattle. This institution is situated in a vibrant tech hub, home to major industry leaders like Microsoft and Amazon, both of which are headquartered in its metropolitan area.

With over 17 years of expertise in software development and data analysis, Prof. Marcelo is deeply passionate about leveraging data to enhance decision-making processes. His impressive career includes significant contributions to Tableau and Microsoft, where he worked on diverse teams, including C#, C++, and Azure.

In this episode, Prof. Marcelo will explore the topic ‘The Evolution of Algorithms: From Classic to Cutting-Edge Techniques.’ He will guide us through the captivating journey of algorithm development, emphasizing the progression from foundational concepts to the latest innovative techniques in the field.

About the Guest:

Prof. Marcelo Guerra Hahn brings over 17 years of expertise in software development, data analysis, testing, and project management to the table. His enthusiasm for data and its role in enhancing decision-making processes is evident in his work. Marcelo has previously led the engineering team at SoundCommerce, a startup focused on data analysis for e-commerce businesses and has also made significant contributions at Tableau and Microsoft. He holds multiple advanced degrees, including a master’s in computer science from the Universidad de la República in Uruguay, an MBA, and a master’s in applied mathematics from the University of Washington, as well as a master’s in applied statistics from Texas A&M.

This podcast is brought to you by Global Management Consultancy. For more information, please visit www.globalmanagementconsultancy.com.

Disclaimer:

A. The background music used in this video is the property of its respective developer and is protected by Copyright. Although it is a free version, Business Talk, Global Management Consultancy and Deepak Bhatt do not hold the rights to this music.

B. Prof. Marcelo Guerra Hahn has granted permission to share insights from the topic, “The Evolution of Algorithms: From Classic to Cutting-Edge Techniques” on Business Talk Podcast Channel. The uploaded video contains copyrighted material; therefore, any modifications to graphics, music, or the presence of the author or host are strictly prohibited.

Prof Marcelo Guerra Hahn explores from Basics to Breakthroughs The Evolutionary Path of Algorithms

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Data, Insight, and Prediction: The Sense-Making Paradox

Welcome to an overview of Sense-Making in AI, exploring the central paradox that defines modern business intelligence: We are drowning in data and starving for insight.
Despite the explosion of information—with 90% of all data created in the last two years (a figure only growing with AI)—most organizations still utilize less than 5% of their total data for critical decision-making. What stands between this massive volume of data and genuine business meaning?

This segment explains the important shift from seeing AI just as a tool for automation to recognizing its true power as a sense-maker. We explain how Artificial Intelligence finds patterns and predicts results, allowing systems to learn and potentially improve their own learning. However, the pursuit of insight requires the essential element of Human Intelligence, which adds context, ethics, and creativity. Data shows you what happened, AI predicts what’s next, but humans decide what matters most. The most valuable insights are found where AI and humans meet. You will learn how to turn a simple pattern detected by AI into a practical business decision. We focus on the formula: “Insight = Pattern + Purpose.” An actionable insight must be surprising yet simple, backed by data and context, and lead to a specific action. While facts describe, insights explain and inspire agility in business.

Ultimately, this overview helps you understand the connection between Pattern, Meaning, and Decision, making sure that AI’s predictions are turned into hypotheses that lead to experimentation and business success.

The_Data_Paradox__Synthetic_AI,_The_Reality_Gap,_and_the_Human_

Des parcours Data et IA inspirants, des conseils, des technologies qui changent le monde, tout ça dans un format ludique !

Welcome to Business Talk, your go-to podcast for the latest trends, insights, and thought-provoking discussions in the business world. Whether you're a business professional, entrepreneur, researcher, or academic, our episodes will challenge you to rethink conventional wisdom and inspire actionable ideas.

Brought to you by Global Management Consultancy, we are committed to driving innovation and excellence in the business community. All content Copyrighted 2024 by Global Management Consultancy.

For more information about our past and upcoming podcasts, please click here:https://www.deepakbbhatt.com/businesstalk

New tracks tagged ##DataScience