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 WebsiteT5: 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 WebsiteFor 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.
