This repository contains the material for the tutorial for the ICAART 2021 Conference. This tutorial will take place on the 4th of February 2021 at 16:15-18:15 (Zürich Time). In case of any question you can reach me at umberto.michelucci@toelt.ai (www.toelt.ai) any time. Our latest publications can be found HERE.
The program can be found AT THIS LINK.
In this folder you will find examples in form of Jupyter Notebooks. You don't need to install anything locally on your computer to try them out. Simply click on the link below, and they will open in Google Colab (What is google colab). During the tutorial I will briefly cover what is google colab.
For those of you a bit more advanced, here is a notebook where you can play with your first autoencoder
Your first Autoencoder with keras
In the file Introduction_to_Jupyter_Colab_GitHub.pdf that you can find in this folder, you can find a very good introduction to Google Colab and what are Jupyter notebooks by Michela Sperti.
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You can find an introduction to Neural Networks in the slides for a lecture given by Umberto Michelucci at the ETH in Zürich, Switzerland. They are google slides and should be accessible online easily.
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In this repository in GitHub you can find the complete material of a course given by Umberto Michelucci at the University of Applied Science in Zürich in 2019. Note that the code is still a mixture of TensorFlow 1.x and 2.x (at the time TensorFlow 2.X was not as mature as now).
Deep Learning Course Material - 2019 - ZHAW - GitHub Repository
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In this repository in GitHub you can find the material for a series of 4 seminars for PhD students at the ETH in Zürich at the exo-planets Astrophysics Department with Prof. S. Quanz.
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I am working on the 2nd edition of my book Applied Deep Learning by Apress. It will come out in 2022 but there is an online version that will grow in 2021 with more and more material. You can check it out here
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A Github repository (by Umberto Michelucci) on how to approach TensorFlow 2.X. Here you can find how to study it, various examples and code that you can study and try yourself.
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In this presentation you can find the most important features of keras, the library now part of TensorFlow to build, develop and train neural networks. This is the library that we have used in all the examples.
This GitHub Repository contains the two days workshop I held in London at the O'Reilly Conference on Convolutional Neural Network. There is lots of material (basic and advanced) for you to check out.
The material is (C) 2021 of Umberto Michelucci, co-founder and chief AI Scientist www.toelt.ai.
