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Deep Learning: a hands-on introduction

  • Duration
    20 hours

    Nicoletta Noceti - University of Genoa (DIBRIS) -

    13-17 July 2020, 9:00-13:00

    Via Dodecaneso 35, room TBA

    Deep Learning is a branch of Machine Learning that has recently achieved astonishing results in a number of different domains. This course will provide a hands-on introduction to Deep Learning, starting from its foundations and discussing the various types of deep architectures and tools currently available.

    The theoretical classes will be accompanied by work in lab (with Python using Keras and Tensorflow), which will constitute an integral part of the course, giving the possibility of practicing deep learning with examples from real-world applications, with particular focus on visual and temporal data. Besides well established approaches, the course will also highlight current trends, open problems and potential future lines of research

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    Detailed Program References


  • Mon, Jul 13

    Class 1
    Machine Learning reprise + Introduction to deep learning: From single layer perceptron to deep neural networks

    Lab 1

  • Tue, Jul 14

    Class 2
    Convolutional neural networks

    Lab 2

  • Wed, Jul 15

    Class 3
    Dealing with time data: Recurrent Neural Networks and Long-Short Term Memory

    Lab 3
    RNN + LSTM

  • Thu, Jul 16

    Class 4
    Generative Adversarial Networks

    Lab 4

  • Fri, Jul 17

    Examples of applications to real world problems, open issues


Slides, notebooks, and a list of bibliographical references and additional material will be provided to attendants.
All the course material is in English.

    • Goodfellow, Y. Bengio and A. Courville, Deep Learning book, MIT Press, 2016.

    • Francois Chollet. Deep Learning with Python, Manning Pub., 2017.