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Ditch Excel, Embrace AI: Why Python is the Future for Finance Pros - Stephanie Mertz | Ep.063

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Manage episode 409078114 series 3442672
Indhold leveret af Adam Shilton. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Adam Shilton eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

In this episode of Tech for Finance, we interview Stephanie Mertz, co-founder and CTO of Eisen, an innovative fintech platform aiming to transform dormant account management. With deep expertise in computer science and financial technology, Stephanie shares her perspectives on leveraging AI tools to solve problems, building resilient systems, the requirement for foundational knowledge, and more. Tune in to hear Stephanie's thoughts on moving beyond traditional finance tools like Excel, considerations around automation platforms, prompt engineering in AI, and the future of generative AI. Whether you're a seasoned finance pro or just starting out, you'll come away with fresh ideas to level up your technical skills. ------ SHOW NOTES ------ - Connect with Steph on LinkedIn - https://www.linkedin.com/in/stephmertz/ - Check out Eisen - https://www.witheisen.com/ ------ CHAPTERS ------ Here is a summary of the key chapters in the transcript: (00:00:00) - Introduction to Stephanie and Aizen (00:01:41) - Stephanie's background and experience (00:03:30) - Stephanie's approach to solving problems (00:05:37) - Starting the development process (00:08:29) - Using AI tools versus Excel (00:10:40) - Criticality levels for automation (00:12:00) - Understanding code from AI assistants (00:16:07) - Backup plans for critical systems (00:20:23) - Version control and documentation (00:26:29) - Case study on using ML for sentiment analysis (00:29:07) - The need for foundational knowledge (00:31:35) - Training machine learning models (00:35:09) - Security risks from deepfakes (00:38:15) - Using Python for analytics (00:40:00) - Levels of automation tools (00:42:17) - Engineering principles for critical systems (00:49:46) - Advice on starting coding projects (00:52:31) - The future of prompt engineering (00:54:01) - One-shot vs. two-shot prompting (00:58:27) - Explaining dormant accounts and Eisen (01:00:14) - Favorite productivity tools For more goodies, check out www.techforfinance.com

  continue reading

73 episoder

Artwork
iconDel
 
Manage episode 409078114 series 3442672
Indhold leveret af Adam Shilton. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Adam Shilton eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

In this episode of Tech for Finance, we interview Stephanie Mertz, co-founder and CTO of Eisen, an innovative fintech platform aiming to transform dormant account management. With deep expertise in computer science and financial technology, Stephanie shares her perspectives on leveraging AI tools to solve problems, building resilient systems, the requirement for foundational knowledge, and more. Tune in to hear Stephanie's thoughts on moving beyond traditional finance tools like Excel, considerations around automation platforms, prompt engineering in AI, and the future of generative AI. Whether you're a seasoned finance pro or just starting out, you'll come away with fresh ideas to level up your technical skills. ------ SHOW NOTES ------ - Connect with Steph on LinkedIn - https://www.linkedin.com/in/stephmertz/ - Check out Eisen - https://www.witheisen.com/ ------ CHAPTERS ------ Here is a summary of the key chapters in the transcript: (00:00:00) - Introduction to Stephanie and Aizen (00:01:41) - Stephanie's background and experience (00:03:30) - Stephanie's approach to solving problems (00:05:37) - Starting the development process (00:08:29) - Using AI tools versus Excel (00:10:40) - Criticality levels for automation (00:12:00) - Understanding code from AI assistants (00:16:07) - Backup plans for critical systems (00:20:23) - Version control and documentation (00:26:29) - Case study on using ML for sentiment analysis (00:29:07) - The need for foundational knowledge (00:31:35) - Training machine learning models (00:35:09) - Security risks from deepfakes (00:38:15) - Using Python for analytics (00:40:00) - Levels of automation tools (00:42:17) - Engineering principles for critical systems (00:49:46) - Advice on starting coding projects (00:52:31) - The future of prompt engineering (00:54:01) - One-shot vs. two-shot prompting (00:58:27) - Explaining dormant accounts and Eisen (01:00:14) - Favorite productivity tools For more goodies, check out www.techforfinance.com

  continue reading

73 episoder

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