Before we begin, let us talk about how Mike (a fictional character) spends a typical morning. Mike begins his day by searching for breakfast recipes on Google Now (https://en.wikipedia.org/wiki/Google_Now). After a filling breakfast, Mike starts getting ready for work. He asks Siri (http://www.apple.com/in/ios/siri/) to tell him the weather and traffic conditions for his drive to work. Finally, as Mike gets ready to leave the house, he asks Alexa (https://en.wikipedia.org/wiki/Amazon_Alexa) to dim the lights and thermostat. It is not even 10 a.m. yet, but Mike like many of us has already used three intelligent personal assistant applications using Natural Language Processing (NLP). We will unravel the mysteries of building intelligent personal assistants with a simple example to build such an assistant quite easily using NLP.
Python is a very powerful programming language that understands structural, functional and object oriented programming paradigms. New comers to Python from other languages tend to carry with them their mother (programming) tongue culture. Although they achieve the required task, they might have fallen in the trap of using Python the wrong way. In this post, we cover some efficient tricks to achieve tasks in Python; we call it the Pythonic way. Find an IPython Notebook for all tricks here on our GitHub repository.
Lists, Tuples, Dictionaries and Sets
Long, long time ago … I started with Octave and Matlab.They were amazing and allowed me to solve a lot of interesting problems in my research. I loved the command window of Octave, but I needed the productivity an IDE gives when developing complex calculations. None of the available IDE’s for Octave were not as powerful as the Matlab IDE. The problem was that Matlab was not GNU and buying a license was very expensive. Then, I found R and I realized that none Octave neither Matlab were the tool I needed for my research. I needed advanced project and file management through repositories, fast data manipulation, an easy way to export my calculations, a creative way of authoring reports and a powerful IDE that let me access my beloved command window. Now R gives me all I need and is an important part of my everyday toolbox. For those who does not known R, I must say that R is a well known programming language that is widely used on mathematics, economy, biology… Its main benefits includes the ability to work easily with statistics and data manipulation. R is very popular on academics and research, is GNU, very powerful and have a lot of packages that allows do magical things in a few clicks or with a few commands.
More than 150 professionals, researchers and students come to that series of Conferences, known to be in the top of the Spanish HCI Conferences with the sponsoring of SCHI, the ACM and the AIPO organizations. These series of Conferences shows the work of 105 publications of 22 differents countries. Continue reading
Static analysis is a method that one can use in order to analyze, understand, and assess the quality of a program. The main strength of static analysis is the pinpointing of coding errors without the execution of a program. In this blog post, we discuss how static analysis can contribute to the evaluation of the existing exceptions of a program and how static analysis can help in the prediction of possibly thrown exceptions by a program.