Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Plan du cours
- Backprop, modèles modulaires
- Module Logsum
- RBF Net
- Perte MAP/MLE
- Transformations de l'espace des paramètres
- Module convolutionnel
- Apprentissage basé sur le gradient
- Énergie pour l'inférence
- Objectif de l'apprentissage
- ACP, NLL
- Modèles de variables latentes
- LVM probabiliste
- Fonction de perte
- Reconnaissance de l'écriture manuscrite
Pré requis
Bonnes bases en apprentissage automatique. Compétences en programmation dans n'importe quel langage (idéalement Python/R).
21 heures
Nos Clients témoignent (4)
The structure from first principles, to case studies, to application.
Margaret Webb - Department of Jobs, Regions, and Precincts
Formation - Introduction to Deep Learning
The deep knowledge of the trainer about the topic.
Sebastian Görg
Formation - Introduction to Deep Learning
I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.
Radek
Formation - Introduction to Deep Learning
Exercises after each topic were really helpful, despite there were too complicated at the end. In general, the presented material was very interesting and involving! Exercises with image recognition were great.