21 hours (usually 3 days including breaks)
Good grounding in basic machine learning. Programming skills in any language (ideally Python/R).
This course is general overview for Deep Learning without going too deep into any specific methods. It is suitable for people who want to start using Deep learning to enhance their accuracy of prediction.
- Backprop, modular models
- Logsum module
- RBF Net
- MAP/MLE loss
- Parameter Space Transforms
- Convolutional Module
Energy for inference,
Objective for learning
- Latent Variable Models
- Probabilistic LVM
- Loss Function
- Handwriting recognition
The topic is very interesting.
Trainers theoretical knowledge and willingness to solve the problems with the participants after the training.
Topic. Very interesting!.
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.
I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.
The subject. It seemed interesting, but I left knowing not much more than before.
I liked that this course had very interesting subject.
The deep knowledge of the trainer about the topic.
Bookings, Prices and Enquiries
|Number of Delegates||Private Remote|
|Number of Delegates||Public Classroom|
|Location||Date||Course Price [Remote/Classroom]|