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Featured: Women in Tech Global Conference 2026 Virtual-first
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12-15 May 2026
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  1. Speaker
  2. Sasha
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WOMEN IN TECH GLOBAL CONFERENCE 2021

Sasha Schriber

CEO at Nanos AI

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"Machine Learning Company 101 - How To Create a Tech Startup from Scratch"

Tue June 8 - 4:50 AM EDT/New York (See in local time)
Add to Calendar 05//2025 4:50 AM 05//2025 05:30 AM America/New_York #WTGC2025

"Machine Learning Company 101 - How To Create a Tech Startup from Scratch"
#WTGC2025

"Machine Learning Company 101 - How To Create a Tech Startup from Scratch"
https://www.womentech.net/ringcentral
https://www.womentech.net/ringcentral
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Session: Machine Learning Company 101 - How To Create a Tech Startup from Scratch

This is a hands-on non-tech talk about how to build a machine learning company from scratch. It touches upon several key aspects of building and running a tech startup - product, data, hiring, stocks, fundraising, and marketing.


Key Takeaways

  • Can I start a machine learning company if I have no technical background?
  • How do I figure out if the product I am going to build for my future clients can be developed with software or is there a strong need for machine learning technology?
  • How and where do I hire the best machine learning talent that I can afford for my new, awesome tech idea?
  • How has the pandemic changed the way ML startups used to work, hire or raise money?
  • What do I do if I have no previous data to start with?


Bio

Sasha Schriber is CEO and founder of NANOS.AI, a machine learning startup based in Switzerland. Nanos turns the process of creating and placing online advertisements into a simple, automated, and transparent action by using machine learning. A former Walt Disney Imagineering cast member, she also founded and developed an innovation group within Disney Research in collaboration with the Federal Institute of Technology (ETH). Background in math, finance, and law; 20+ patents in multimedia, previsualisation, machine learning, and online marketing technologies, and publications at ACM IUI, IEEE InfoVis, IAAI, ICIDS.

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