Applied deep learning  

The aim of this course is to provide an overview of modern applications of machine learning and develop practical skills in using deep neural networks for common machine learning tasks. The objective of this course is to provide an introduction into artificial neural network based models, as well as an introduction to existing API frameworks for training such models. Previous knowledge regarding machine learning is not expected. The practical assignments will be developed in Python programming language. The language of instruction is Latvian. Results Knowledge: 1. Describe the main neural network machine learning approaches. (EQUANIE concepts E1-1, E-12) Skills: 2. Independently develop software systems with deep learning solutions. (EQUANIE realization E3-5, practice E5-1) Competencies: 3. Provide examples of suitable applications for machine learning methods and their limitations. (EQUANIE concepts E1-4, analysis E2-1) 4. Evaluate practical problems which may require machine learning and propose the appropriate methods to solve them. (EQUANIE analysis E2-3, E2-4)
Presential
English
Applied deep learning
English

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