Prerequisites

Python

For this set of seminary some Python knowledge is necessary to be able to profit from the hands-on sessions. The code is not complicated but requires some experience with Python and TensorFlow Keras (library from Google for neural networks). In case you want to brush up your Python skills (or learn them by scratch) here is a list of resources that you may consider.

• https://www.learnpython.org

• Beginner Guide Python: https://wiki.python.org/moin/BeginnersGuide

• Python for scientists: https://scipy-lectures.org/intro/

Tools

For the seminars all the hands-on session will be carried out in Google Colab. Note that during the seminars we will give an introduction to Google Colab live.

If you have never used it consider watching an introduction to it in the videos and webpages

• https://colab.research.google.com/notebooks/basic_features_overview.ipynb (overview of Google Colab)

• https://www.youtube.com/watch?v=PitcORQSjNM (Introduction to TensorFlow in Google Colab)

Neural Networks and Keras

The topic of neural networks is a complex one and requires some study. You can consult following books for an introduction to Neural Networks and Keras.

• Applied Deep Learning - A Case-Based Approach to Understanding Deep Neural Networks - 1st. Edition

  Michelucci, U., Apress Media, LLC: New York, NY, USA, 2018; ISBN 978-1-4842-3789-2

• Advanced applied deep learning: convolutional neural networks and object detection

  Michelucci, U., Apress Media, LLC: New York, NY, USA, 2019; ISBN 978-1-4842-4975-8

• Hands-On Neural Networks with TensorFlow 2.0
  Galeone, P., Packt Media, ISBN 9781789615555