Plan Szkolenia

Current state of the technology

  • What is used
  • What may be potentially used

Rules based AI 

  • Simplifying decision

Machine Learning 

  • Classification
  • Clustering
  • Neural Networks
  • Types of Neural Networks
  • Presentation of working examples and discussion

Deep Learning

  • Basic vocabulary 
  • When to use Deep Learning, when not to
  • Estimating computational resources and cost
  • Very short theoretical background to Deep Neural Networks

Deep Learning in practice (mainly using TensorFlow)

  • Preparing Data
  • Choosing loss function
  • Choosing appropriate type on neural network
  • Accuracy vs speed and resources
  • Training neural network
  • Measuring efficiency and error

Sample usage

  • Anomaly detection
  • Image recognition
  • ADAS

 

 

 

 

Wymagania

The participants must have programming experience (any language) and engineering background, but are not required to write any code during the course.

  14 godzin

Liczba uczestników


Data rozpoczęcia

Data zakończenia


Daty szkoleń są uzależnione od dostępności trenerów. Szkolenia standardowo odbywają się w godzinach od 09:00 do 16:00.

Cena za uczestnika

Opinie uczestników (1)

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