Data Science at Home

268 Avsnitt

1. MLOps: what is and why it is important Part 2 (Ep. 152)

   Publicerades: 2021-05-19
2. MLOps: what is and why it is important (Ep. 151)

   Publicerades: 2021-05-11
3. Can I get paid for my data? With Mike Andi from Mytiki (Ep. 150)

   Publicerades: 2021-04-28
4. Building high-growth data businesses with Lillian Pierson (Ep. 149)

   Publicerades: 2021-04-19
5. Learning and training in AI times (Ep. 148)

   Publicerades: 2021-04-13
6. You are the product [RB] (Ep. 147)

   Publicerades: 2021-04-11
7. Polars: the fastest dataframe crate in Rust - with Ritchie Vink (Ep. 146)

   Publicerades: 2021-04-08
8. Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)

   Publicerades: 2021-03-26
9. Pandas vs Rust (Ep. 144)

   Publicerades: 2021-03-19
10. Concurrent is not parallel - Part 2 (Ep. 143)

    Publicerades: 2021-03-13
11. Concurrent is not parallel - Part 1 (Ep. 142)

    Publicerades: 2021-03-10
12. Backend technologies for machine learning in production (Ep. 141)

    Publicerades: 2021-03-02
13. How to reinvent banking and finance with data and technology (Ep. 139)

    Publicerades: 2021-02-15
14. What's up with WhatsApp? (Ep. 138)

    Publicerades: 2021-02-07
15. Is Rust flexible enough for a flexible data model? (Ep. 137)

    Publicerades: 2021-02-01
16. Is Apple M1 good for machine learning? (Ep.136)

    Publicerades: 2021-01-25
17. Rust and deep learning with Daniel McKenna (Ep. 135)

    Publicerades: 2021-01-18
18. Scaling machine learning with clusters and GPUs (Ep. 134)

    Publicerades: 2020-12-31
19. What is data ethics? (Ep. 133)

    Publicerades: 2020-12-19
20. A Standard for the Python Array API (Ep. 132)

    Publicerades: 2020-12-08