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Convolutional Neural Networks and Image Processing

Workshop is for people who are looking for hands on experience with deep neural networks for image processing, but they didn’t have any real opportunity to do so yet.
Level
Designed for participants with basic knowledge and experience
intermediate
Course length
1 day
Language
 cz  eu
Course code
PU21110286
Artificial intelligence (AI)
Category:
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Courses with lecturer

Term
Language
Place
Form
?
How and where the course takes place.
Price without VAT
2. 4. 2025 09:00 - 17:00
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: PU21110286-0020
Price without VAT
4 990 Kč
2. 4. 2025 09:00 - 17:00
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: PU21110286-0021
Price without VAT
4 990 Kč
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: PU21110286-0003
Price without VAT
4 990 Kč
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: PU21110286-0004
Price without VAT
4 990 Kč

Course description

Through experiments, we will explore how and why such models work, what are the intuitions behind its’ functionality, and gradually, through simple examples, we’ll come to the models that are commonly used in industry. We will focus on possible use cases for neural net’s internal semantic image representation and how to visualize neural net behavior in the most effective way.

Required knowledge

  • basic knowledge of programing in Python
  • high school level of mathematics
  • Basics of machine learning on the level of our course Introduction to  machine Learning

Course content

  • Back to the history
  • What the convolution is and why it works
  • TensorFlow (designing a simple convolutional neural network)
  • Practical classification task with the Fashion MNIST data set.
  • Experiments with the MSCOCO and ResNet data sets
  • Visualisations using TensorBoards
  • Image classification
  • How to deal with noisy data

Lecturers

Adam Kolář
Adam Kolář

After graduating from Brno University of Technology, he spent most of his professional career as a researcher and later as the head of one of the research teams at Seznam.cz. He is currently helping to set up machine learning startups for Central Europe AI and is organizing Machine Learning Meetups Brno.

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Contact us

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Previous courses

Follow-up courses

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