Python – Neural Networks with the TensorFlow Library

Course/Event Essentials

Event/Course Start
Event/Course End
Event/Course Format
Online
Live (synchronous)

Venue Information

Country: Slovakia
Venue Details: Click here

Training Content and Scope

Scientific Domain
Level of Instruction
Intermediate
Advanced
Sector of the Target Audience
Research and Academia
Industry
Public Sector
Other (general public...)
HPC Profile of Target Audience
Application Users
Application Developers
Language of Instruction

Other Information

Organiser
Supporting Project(s)
EuroCC2/CASTIEL2
Event/Course Description

Course contents:

  • Theoretical introduction to the issue (Principles of artificial intelligence and continuous learning)

  • Basics of TensorFlow (syntax, graphs, variables...) and SciKit Learn library

  • Tensorflow – models, activation functions, loss functions, layers, initializers,

    metrics, callbacks, optimizers...

  • Importing data

  • Examples of classification and regression models

  • Text classification

  • Image classification by a convolutional neural network

  • Design, selection and evaluation of different models