Introduction

At TOELT we teach regularly at various international universities. In our courses we cover Machine Learning, Statistics, Deep Learning, Programming, TensorFlow and Keras, Research, Academic Writing, Innovation and much more.

Leading Role in the continuing education in Switzerland

Umberto Michelucci is also a co-lead for two continuing education offering at the University of Lucerne: the certificate of advanced studies in Machine Learning and the certification of advanced studies in data science.

Structure of this page

The courses and lectures listed here are diveded by level: PhD, master, bachelor and Continuing Education .

Books

Umberto Michelucci has published 3 books with Springer Nature on Deep Learning and TensorFlow that have received more than 100 citations and has been downloaded more than 100000 times. He is also writing a fourth book (that will be available end of 2023) that will be a unversity text book for scientists, to enable them to apply machine learning in their research projects.

Book References

Deep Learning for Natural Sciences. (2023). [Book]. In Springer Nature. Springer Nature.

@book{michelucci2023book,
  title = {Deep Learning for Natural Sciences},
  journal = {Springer Nature},
  year = {2023},
  publisher = {Springer Nature},
  link = {},
  bibtex_show = {true},
  abbr = {Book},
  type = {Book},
  topic = {mltheory}
}

Michelucci, U. (2022). Applied Deep Learning with TensorFlow 2 [Book]. Springer Nature/Apress.

[Bibtex]

@book{michelucciapplied,
  title = {Applied Deep Learning with TensorFlow 2},
  author = {Michelucci, Umberto},
  publisher = {Springer Nature/Apress},
  year = {2022},
  abbr = {Book},
  topic = {mltheory},
  type = {Book},
  selected = {true},
  bibtex_show = {true}
}

Michelucci, U. (2019). Advanced applied deep learning: convolutional neural networks and object detection [Book]. Springer Nature.

@article{michelucci2019advanced,
  title = {Advanced applied deep learning: convolutional neural networks and object detection},
  author = {Michelucci, Umberto},
  year = {2019},
  publisher = {Springer Nature/Apress},
  journal = {Springer Nature},
  link = {https://www.apress.com/gp/book/9781484249758},
  bibtex_show = {true},
  abbr = {Book},
  type = {Book},
  topic = {mltheory}
}

Michelucci, U. (2018). Applied Deep Learning - A Case-Based Approach to Understanding Deep Neural Networks [Book]. In Springer Nature. Springer Nature/Apress.

@book{michelucci2018applied,
  title = {Applied Deep Learning - A Case-Based Approach to Understanding Deep Neural Networks},
  author = {Michelucci, Umberto},
  journal = {Springer Nature},
  year = {2018},
  publisher = {Springer Nature/Apress},
  link = {https://www.apress.com/gp/book/9781484237892},
  bibtex_show = {true},
  abbr = {Book},
  type = {Book},
  topic = {mltheory}
}

PhD Level Courses

Deep Learning meets (astro)-Physics

Eidgenössische Technische Hochschule Zürich (ETH Zürich), Technical workshop for the astrophysics department in collaboration with Prof. S. Quanz (January 2020)