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Saturday, July 18 • 4:00pm - 7:00pm
The use of Keras with Tensor Flow applied to neural models and data analysis

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Cecilia Jarne:

Zoom link (updated July 18th)
Meeting ID: 661 8352 0802
Password: 786716

Video: https://www.youtube.com/watch?v=5mKF6HGOvgs

Slides and excersices in the Tutorial Website

T5: This tutorial will help participants implement and explore simple neural models using Keras [1] as well as the implementation of neural networks to apply Deep learning tools for data analysis. It will include an introduction to modeling and hands-on exercises. The tutorial will focus on using Keras which is an open-source framework to develop Neural Networks for rapid prototyping and simulation with TensorFlow [2] as backend. The tutorial will show how models can be built and explored using python. The hands-on exercises will demonstrate how Keras can be used to rapidly explore the dynamics of the network.

Keras is a framework that greatly simplifies the design and implementations of Neural Networks of many kinds (Regular classifiers, Convolutional Neural Networks, LSTM among others). In this mini-course we will study implementations of neural networks with Keras split into two sections: On one side we will introduce the main features of Keras, showcasing some examples; and in then we will do a set of two guided on-line hands-on with exercises to strengthen the knowledge.

Tutorial Website
For this tutorial, you will need basic knowledge of NumPy, SciPy, and matplotlib. To be able to carry out the tutorial, students need a laptop with Linux and these libraries installed:
  • Python
  • Numpy
  • SciPy
  • Matplotlib
  • Scikit learn
  • TensorFlow
  • Keras
I recommend the following sites where is explained the installation of following packages that include a set of the named libraries and some additional tools:
  • https://www.anaconda.com/distribution/
  • https://www.tensorflow.org/install/
  • https://keras.io/
[1] Francois Chollet et al. Keras. https://keras.io, 2015.
[2] Martín Abadi, et al. TensorFlow: Large-scale machine learning on heterogeneous systems, 2015.

avatar for Cecilia Jarne

Cecilia Jarne

Researcher and Professor, Departement of Science and Technology, National University of Quilmes and CONICET
My main research area is the study of the dynamical aspects of Recurrent Neuronal Networks trained to perform different bio-inspired tasks and decision making. I study training methods, implementations and how different degrees of damages affect trained networks. My second research... Read More →

Saturday July 18, 2020 4:00pm - 7:00pm CEST
Link (T5)