Informática, ¿cuál es su futuro?

2017-12-04T19:00:32+00:00 December 2nd, 2017|

Informática, ¿cuál es su futuro? La semana pasada nos visitó Oriol Vinyals  para deleitar a nuestros alumnos del curso Deep Learning for Artificial Intelligence gracias a la complicidad del Barcelona Supercomputing Center (BSC-CNS) al invitarlo a través de su programa Severo Ochoa Research Seminars. Esta vez además propusimos abrirlo a modo de meetup a todos los interesados en el tema.  Pues bien, un éxito, el auditorio de la UPC en el Vertex, acabó abarrotado, con gente en la waiting list que no pudo asistir (nuestras excusas a todos ellos).  En la presentación Oriol nos habló del AlphaGo Zero y cómo se ha convertido en el mejor jugador del mundo usando técnicas de Reinforcement Learning, Deep Learning, etc . A diferencia de sus versiones anteriores de AlphaGo en donde aprendió [...]

Conferencia sobre Deep Learning en Barcelona con la visión de Google DeepMind y Facebook

2017-11-12T15:46:09+00:00 November 12th, 2017|

    A menudo me llegan peticiones de antiguos alumnos o compañeros del sector para poder asistir a alguna de nuestras clases de Deep Learning en la UPC. Por esta razón, junto con Xavier Giró-i-Nieto, y en el marco del curso Deep Learning for Artificial Intelligence del master MET de la escuela de Telecos de la UPC  y de los seminarios Severo Ochoa Research Seminars  del Barcelona Supercomputing Center, hemos creído oportuno realizar una clase abierta  a todos los interesados en el tema, aprovechando que el próximo lunes 20 de Noviembre a las 11:30 tenemos dos participantes de excepción.   En esta clase abierta (en inglés) se presentaran algunos de los últimos avances en el tema desde el punto de vista de dos laboratorios de investigación punteros, como son Google Deepmind y Facebook [...]

Deep Neural net with Keras on a GPU Cloud

2017-11-08T20:36:28+00:00 October 3rd, 2017|

Run a DNN with Keras on Google Cloud In reality, this post was intended for my DLAI course's students, although I think it may be of interest to other students. I am going to share in this blog the teaching material that I am going to generate for the part of DLAI course that will cover the basic principles of Deep Learning from a computational perspective. VGG-19 VGG-19 is a deep convolutional network for object recognition developed and trained by Oxford's renowned Visual Geometry Group (VGG), which achieved very good performance on the ImageNet dataset. You can check Karen Simonyan and Andrew Zisserman publication: Very Deep Convolutional Networks for Large-Scale Image Recognition. Cifar-10 The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images [...]

First steps with PyTorch

2017-10-29T16:40:37+00:00 October 3rd, 2017|

First steps with PYTORCH In reality, this post was intended for my DLAI course's students, although I think it may be of interest to other students. I am going to share in this blog the teaching material that I am going to generate for the part of DLAI course that will cover the basic principles of Deep Learning from a computational perspective. This post provides a fast-paced introduction to the PyTorch API required to follow the DLAI Labs (Master Course at UPC - Autumn 2017). I will teach the part of DLAI course that will cover the basic principles of deep learning from computational perspectives. In this part we will review the basics of Pytorch, the Python implementation of the Torch machine. learning framework PyTorch PyTorch  can be seen [...]

First steps with TensorFlow

2017-11-08T20:41:26+00:00 October 3rd, 2017|

First steps with TensorFlow In reality, this post was intended for my DLAI course's students, although I think it may be of interest to other students. I am going to share in this blog the teaching material that I am going to generate for the part of DLAI course that will cover the basic principles of Deep Learning from a computational perspective. TensorFlow TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. Task 1:  Update DLAI [...]

Factors that have triggered the potential of Deep Learning

2017-11-11T13:37:43+00:00 September 27th, 2017|

Artificial Intelligence and Neural Networks, are not a new concepts! Why, all of a sudden, have them become the next big thing that is changing our life again during this decade? Deep Learning is changing our life I'm sure you have doubtlessly noticed quantum leaps in the quality of a wide range of everyday technologies.   In Speech Recognition  the transcription of voice to text has experimented amazing advances, and it is already available in different devices. We are increasingly interacting with “our” computers by just talking to them.  Also there have been some spectacular advances in Natural Language Processing, for example, by simply clicking on the micro symbol of Google Translate, the system will transcribe what you are dictating to another language. Google Translate now renders spoken sentences in [...]

Programming Models for Deep Learning

2017-09-27T10:08:29+00:00 September 24th, 2017|

Programming Models for Deep Learning In reality, this post was intended for my DLAI course's students, although I think it may be of interest to other students. I am going to share in this blog the teaching material that I am going to generate for the part of DLAI course that will cover the basic principles of Deep Learning from a computational perspective. Recent years, as a result of the increase of the popularity of Deep Learning, many frameworks have surged in order to ease the task of create and train models. Frameworks use different programing languages, strategies to train the models or compute the data and different characteristics as distribution or GPU acceleration support. Most of these frameworks are open sourced and their popularity can be shown in the following Figure from Francesc [...]

First Steps with KERAS

2017-10-24T17:40:12+00:00 September 23rd, 2017|

First steps with KERAS In reality, this post was intended for my DLAI course's students, although I think it may be of interest to other students. I am going to share in this blog the teaching material that I am going to generate for the part of DLAI course that will cover the basic principles of Deep Learning from a computational perspective. This post provides a fast-paced introduction to the KERAS API required to follow the DLAI Labs (Master Course at UPC - Autumn 2017). I will teach the part of DLAI course that will cover the basic principles of deep learning from computational perspectives. In this part we will review the basics of KERAS, a high-level neural networks API, written in Python and capable of running on top of [...]

A stroll through Marenostrum IV computing resources

2017-11-11T13:39:20+00:00 September 18th, 2017|

Enclosed you will find the slides that I used in my last visit to the Torre Girona chapel with UPC students. The slides show the awesome computational power of the Marenostrum IV supercomputer and the presentation of the architecture required to get it.  I have posted these transparencies (and photo) for my students as I promised them. But anyone who wants to know a little more about the Marenostrum can take a look at them to realize the magnitude of this supercomputer.      SLIDESHARE slides <blockquote>In reality, this post was intended for my UPC course's students, although I think it may be of interest to other students.</blockquote>

Getting started with DLAI course labs

2017-10-04T12:20:07+00:00 September 15th, 2017|

Getting Started With DLAI Course Labs In reality, this post was intended for my DLAI course's students, although I think it may be of interest to other students. I am going to share in this blog the teaching material that I am going to generate for the part of DLAI course that will cover the basic principles of Deep Learning from a computational perspective. This post provides a fast-paced introduction to the basic technologies and knowledge required to follow the DLAI Labs (Master Course at UPC - Autumn 2017). I will teach the part of DLAI course that will cover the basic principles of deep learning from computational perspectives. In this part we will review the latests advances in computing platforms, system middleware and DL frameworks required for current [...]

First contact with Keras

2017-10-11T09:24:42+00:00 June 18th, 2017|

. . Keras is a Python library that provides a clean and convenient way to create a range of deep learning models on top of  powerful libraries such as TensorFlow, Theano (update about Theano) or CNTK. Keras was developed and maintained by François Chollet, a Google engineer and it is released under the permissive MIT license. Basic features of Keras (*) I value his austerity and simplicity, without frills approach and maximizing readability. It makes it possible to express neural networks in a very modular way, considering a model as a sequence or a graph alone. A good approximation for beginners, because the components of a Keras model are discrete elements that can be combined in arbitrary ways. New components are intentionally easy to add and modify within [...]