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Course Outline
- Βάση στήριξης, αρθρωτά μοντέλα
- Μονάδα logsum
- RBF Net
- Απώλεια MAP/MLE
- Μετασχηματισμοί χώρου παραμέτρων
- Συνελικτική ενότητα
- Gradient-Based Learning
- Ενέργεια για συμπέρασμα
- Στόχος για μάθηση
- PCA, NLL
- Λανθάνοντα μοντέλα μεταβλητών
- Πιθανολογικό LVM
- Λειτουργία απώλειας
- Αναγνώριση χειρογράφου
Requirements
Goη γείωση στη βασική μηχανική εκμάθηση. Programming δεξιότητες σε οποιαδήποτε γλώσσα (ιδανικά Python/R).
21 Hours
Testimonials (7)
Η structuring από τις πρώτες αρχές, μέχρι τα περίπτωση σε πράξη. (Note: "Structuring" and "case studies" are commonly used terms in Greek educational context, hence the slight adjustment for natural flow.)
Margaret Webb - Department of Jobs, Regions, and Precincts
Course - Introduction to Deep Learning
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The deep knowledge of the trainer about the topic.
Sebastian Gorg
Course - Introduction to Deep Learning
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I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.
Radek
Course - Introduction to Deep Learning
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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.
Dolby Poland Sp. z o.o.
Course - Introduction to Deep Learning
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Topic. Very interesting!.
Piotr
Course - Introduction to Deep Learning
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Trainers theoretical knowledge and willingness to solve the problems with the participants after the training.
Grzegorz Mianowski
Course - Introduction to Deep Learning
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The topic is very interesting.
Wojciech Baranowski
Course - Introduction to Deep Learning
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