Data Science at Home

264 Episodio

1. Episode 24: How to handle imbalanced datasets

   Pubblicato: 09/10/2017
2. Episode 23: Why do ensemble methods work?

   Pubblicato: 03/10/2017
3. Episode 22: Parallelising and distributing Deep Learning

   Pubblicato: 25/09/2017
4. Episode 21: Additional optimisation strategies for deep learning

   Pubblicato: 18/09/2017
5. Episode 20: How to master optimisation in deep learning

   Pubblicato: 28/08/2017
6. Episode 19: How to completely change your data analytics strategy with deep learning

   Pubblicato: 09/08/2017
7. Episode 18: Machines that learn like humans

   Pubblicato: 28/03/2017
8. Episode 17: Protecting privacy and confidentiality in data and communications

   Pubblicato: 15/02/2017
9. Episode 16: 2017 Predictions in Data Science

   Pubblicato: 23/12/2016
10. Episode 15: Statistical analysis of phenomena that smell like chaos

    Pubblicato: 05/12/2016
11. Episode 14: The minimum required by a data scientist

    Pubblicato: 27/09/2016
12. Episode 13: Data Science and Fraud Detection at iZettle

    Pubblicato: 06/09/2016
13. Episode 12: EU Regulations and the rise of Data Hijackers

    Pubblicato: 26/07/2016
14. Episode 11: Representative Subsets For Big Data Learning

    Pubblicato: 03/05/2016
15. Episode 10: History and applications of Deep Learning

    Pubblicato: 14/03/2016
16. Episode 9: Markov Chain Montecarlo with full conditionals

    Pubblicato: 02/03/2016
17. Episode 8: Frequentists and Bayesians

    Pubblicato: 15/02/2016
18. Episode 7: 30 min with data scientist Sebastian Raschka

    Pubblicato: 15/02/2016
19. Episode 6: How to be data scientist

    Pubblicato: 19/01/2016
20. Episode 5: Development and Testing Practices in Data Science

    Pubblicato: 13/01/2016