A series of webinars “Deep Learning: everything you wanted to know about “Deep Learning”

30.05.2021 02:19

A series of webinars “Deep Learning: everything you wanted to know about “Deep Learning”
On June 2, 2021, we will launch a series of three webinars on Deep Learning.
Speaker: Yevhen Fedorov, Doctor of Technical Sciences, Professor at Department of Robotics and Specialized Computer Systems at Cherkasy State Technological University, an author of over 170 scientific and scientific-methodological papers, 15+ monographs and 20+ publications in Scopus, Web of Science, DBLP.
We invite students, postgraduate students and everyone who is interested in deepening their knowledge in the field of deep learning
Please register via the link | Participation is free of charge.
Topic: “Deep Learning: everything you wanted to know about “Deep Learning”
Key points of the webinar:

● Different types of neural networks;
● Google Colab environment;
● Relevance/importance of Deep learning in programming and engineering.
The following auxiliary issues will be considered for the participants:
● fundamental knowledge of Python;
● basic knowledge in the field of Deep learning;
● urge to quickly learn how to implement the algorithms of Deep learning.
Why is this topic important?
Most of innovative projects have Deep learning component, which makes the need to study new trends in this area more relevant.
Deep Learning is used to work with homogeneous signals (like speaking), two-dimensional signals — images, and three-dimensional signals — video. In addition, the fields of application are: processing of hand-written text, biometric identification of a person (by voice, face, etc.), analysis of medical images (for example, mammography, and tomogram). As a rule, Deep Learning is used alongside with the technology of parallel processing of information CUDA for GPU, which ensures accurate, reliable and quick learning.

Timing (webinar No.1) — June 2 (Wednesday), 
4.00 p.m.
Venue: online, Zoom
Participation is free of charge, subject to prior registration: https://bit.ly/NESWebinarRegistration