Kursplan
Introduksjon
Sannsynlighetsteori, modellvalg, beslutnings- og informasjonsteori
Sannsynlighetsfordelinger
Lineære modeller for regresjon og klassifisering
Neural Networks
Kjernemetoder
Sparsomme kjernemaskiner
Grafiske modeller
Blandingsmodeller og EM
Omtrentlig slutning
Prøvetakingsmetoder
Kontinuerlige latente variabler
Sekvensielle data
Kombinere modeller
Oppsummering og konklusjon
Krav
- Forståelse av statistikk.
- Kjennskap til multivariatregning og grunnleggende lineær algebra.
- Noe erfaring med sannsynligheter.
Publikum
- Dataanalytikere
- PhD-studenter, forskere og praktikere
Testimonials (5)
Very flexible.
Frank Ueltzhöffer
Kurs - Artificial Neural Networks, Machine Learning and Deep Thinking
I liked the new insights in deep machine learning.
Josip Arneric
Kurs - Neural Network in R
I really appreciated the crystal clear answers of Chris to our questions.
Léo Dubus
Kurs - Réseau de Neurones, les Fondamentaux en utilisant TensorFlow comme Exemple
Ann created a great environment to ask questions and learn. We had a lot of fun and also learned a lot at the same time.
Gudrun Bickelq
Kurs - Introduction to the use of neural networks
It was very interactive and more relaxed and informal than expected. We covered lots of topics in the time and the trainer was always receptive to talking more in detail or more generally about the topics and how they were related. I feel the training has given me the tools to continue learning as opposed to it being a one off session where learning stops once you've finished which is very important given the scale and complexity of the topic.