Infinite Curiosity Pod with Prateek Joshi

169 Épisodes

1. Data product pyramid, data product marketplace, data mesh | Jon Cooke

   Publié: 29/09/2022
2. Building a collaborative data platform, founding a startup, product design, engaging users, how will data roles evolve in the future | Oliver Hughes

   Publié: 26/09/2022
3. Data observability, building a data startup, how to do customer discovery | Egor Gryaznov

   Publié: 22/09/2022
4. Synthetic data, quality profiling, building a data startup | Fabiana Clemente

   Publié: 19/09/2022
5. Building an open source startup, programming hygiene for ML practitioners, product discipline | Ketan Umare

   Publié: 15/09/2022
6. Investing in ML startups, building ML products, startup opportunities in ML | Leigh Marie Braswell

   Publié: 12/09/2022
7. How to build an ML startup from scratch, product design, open source strategy, pricing mechanics | Phil Howes

   Publié: 08/09/2022
8. Building a global community for women in AI and tech | Sadie St. Lawrence

   Publié: 01/09/2022
9. Growing from 0 to 775,000 YouTube subscribers by teaching ML and statistics | Joshua Starmer

   Publié: 29/08/2022
10. Building low-code ML tools, being a second-time founder | Tommy Dang

    Publié: 22/08/2022
11. Investing in ML and Data startups, Understanding the modern data stack | Chad Sanderson

    Publié: 15/08/2022
12. AI in pharma, Building products for pharma vs bio vs healthcare | John Thompson

    Publié: 08/08/2022
13. Active Learning in ML, DataPrepOps, Carbon footprint of AI systems | Jennifer Prendki

    Publié: 01/08/2022
14. Telling stories WITH data vs ABOUT data | Scott Taylor

    Publié: 28/07/2022
15. Upskilling, learning, and keeping yourself relevant as a data practitioner | Matt Harrison

    Publié: 25/07/2022
16. Ben Taylor on metaheuristics, AI teaching AI, genetic programming, impact of generative AI on art, building startups, and what it means to be the first data scientist at a company

    Publié: 21/07/2022
17. Srinath Sridhar on the 0-to-1 journey of building ML products

    Publié: 18/07/2022
18. What's new in ML: Space telescope, rare earth elements, universal speech translator, quantitative reasoning, quantum computing, robots handling deformable material, and how AI systems can explain a pi

    Publié: 14/07/2022
19. Adam Sroka on how energy markets work, where renewable energy fits in, software engineering, data scientists, and using machine learning for climate problems

    Publié: 11/07/2022
20. Doug Laney on infonomics, data monetization patterns, quantifying data's economic value, collateralizing data, and insuring data.

    Publié: 06/07/2022