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MFN0824 - Notebooks and other materials for the practical part of the Neural Networks course (Physics Dept. @ Unito)

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Neural Networks Course (MFN0824)

This repository contains the Jupyter notebooks and other materials used for the Neural Networks course, held at the Physics Department of the University of Turin. You can find more details on the institutional page of the course. More notebooks and materials will be added along the course.

NOTE: The "appendix" notebooks, beginning with capital letters, are meant to be a review of basic concepts that will be used during the course. They should therefore be completed before looking at the numbered notebooks, which contain the course material instead.


Looking at the Notebooks

For some reason, github does not render the notebooks in the correct way. If you just want to take a look at the rendered notebooks without running the code, please use the Jupyter Notebook Viewer service. You can access the notebooks in this directory directly by clicking on the badge at the top of the page or here: Open In nbviewer .


Running the Notebooks

The notebooks can be run both locally on your computer or online using Google Colab.

  • Colab Notebooks

The Colab service can be accessed for free with any personal google account, including your institutional one (@edu.unito.it, @unito.it), and provides an interactive Jupyter notebook environment. Many of the most used python libraries are pre-installed and can be used in a straightforward manner after a simple import statement. The Colab main page is also a good starting point both if you need to gain a bit of confidence with the basics of Jupyter notebook and if you want to take a look at some nice examples and tutorials.

You can load a copy of the entire directory in colab by clicking on the following badge: Open In Colab A similar badge will be present in each notebook and allows you to open a copy of the the notebook directly in Colab. Note that, in order to retain your work, you will need to save the notebooks before you close them.

  • Jupyter Notebooks on a Local Machine

You can also run the notebooks by cloning this github repository on your local machine or by downloading it in the compressed version. In this case, in order to run the notebooks it is advised that you download and install the latest Anaconda Distribution which will provide you with a lot of useful packages, including Jupyter notebooks, Numpy and Matplotlib. You will have to install Tensorflow2 manually after installing Anaconda, in order to do so just open a terminal and type:

conda install tensorflow

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