DataTalks.Club

166 Episodio

1. Cracking the Code: Machine Learning Made Understandable - Christoph Molnar

   Pubblicato: 26/11/2023
2. The Unwritten Rules for Success in Machine Learning - Jack Blandin

   Pubblicato: 20/11/2023
3. From a Research Scientist at Amazon to a Machine learning/AI Consultant - Verena Webber

   Pubblicato: 10/11/2023
4. From Marketing to Product Owner in Search - Lera Kaimashnіkova

   Pubblicato: 05/11/2023
5. Collaborative Data Science in Business - Ioannis Mesionis

   Pubblicato: 27/10/2023
6. Bridging Data Science and Healthcare - Eleni Stamatelou

   Pubblicato: 20/10/2023
7. DataTalks.Club Anniversary Interview - Alexey Grigorev, Johanna Bayer

   Pubblicato: 12/10/2023
8. Data Engineering for Fraud Prevention - Angela Ramirez

   Pubblicato: 06/10/2023
9. From Data Manager to Data Architect - Loïc Magnien

   Pubblicato: 29/09/2023
10. Pragmatic and Standardized MLOps - Maria Vechtomova

    Pubblicato: 08/09/2023
11. Democratizing Causality - Aleksander Molak

    Pubblicato: 25/08/2023
12. Mastering Data Engineering as a Remote Worker - José María Sánchez Salas

    Pubblicato: 18/08/2023
13. The Good, the Bad and the Ugly of GPT - Sandra Kublik

    Pubblicato: 04/08/2023
14. LLMs for Everyone - Meryem Arik

    Pubblicato: 28/07/2023
15. Investing in Open-Source Data Tools - Bela Wiertz

    Pubblicato: 21/07/2023
16. Why Machine Learning Design is Broken - Valerii Babushkin

    Pubblicato: 14/07/2023
17. Interpretable AI and ML - Polina Mosolova

    Pubblicato: 07/07/2023
18. From Scratch to Success: Building an MLOps Team and ML Platform - Simon Stiebellehner

    Pubblicato: 30/06/2023
19. From MLOps to DataOps - Santona Tuli

    Pubblicato: 23/06/2023
20. Data Developer Relations - Hugo Bowne-Anderson

    Pubblicato: 16/06/2023