Archives 2016

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Sentiment Analysis of French texts using deep learning techniques

In this blog, we will see how deep learning techniques (Recurrent Neural Network, RNN and/or Convolutional Neural Network, CNN) can be used to determine the sentiment polarity of a written text.  This is call "sentiment analysis" and it's very useful to enhanced the communication with your customers.  Such algorithms are typically used to analyze emails, website or even Facebook posts where your customers may talk about your products. Thanks to this, you can prioritize your answers and react faster to the unsatisfied customers... ...

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Scrapping social data from Facebook

Nowadays, social networks can be considered as a main source of data.  This is particularly true for business to customer companies which must take into account customer feedback on their products.  In this blog, we will show how to retrieve information from Facebook using the Facebook Graph API... ...

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Scrapping land invest data from dynamic web

In a previous blog post, we have seen how to mine information on static web pages.  In this blog post, I'll explain how we can do the same on dynamically (i.e. javascript) generated web pages.  As a showcase, I will show you how to find the best land investment you can make in Belgium today... ...

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Scrapping movie data from static web

Every data science journey starts by aggregating the data of interest.  In the industry sector, those are often coming directly from sensors, user surveys, software or application used by your customers.  Nonetheless, the information publicly available on the web still remain an important source of additional information like news, weather or even geographical addresses.  Today, we will focus on movie data... ...

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