When it comes to Data Science, the most recurring topic is modeling. Quite a few articles out there talk about data preparation and only a bunch about how to communicate your results properly. However, there are hardly any dealing with the topic that we are going to cover today: data enrichment.
Whether you are from a startup or a big corporation, every company today has one problem in common. At some point, there is a need to develop your own analytic capabilities so you can leverage your data efficiently. While outsourcing and getting help from consultants can be a great way to get things off the ground, eventually it does make sense to have the dedicated people in-house. And voila, you are searching for your first Data Scientist.
For this blog post we decided to jump on the PokémonGO hype and add a bit of science into the craze. Our goal is to give you the optimal portfolio of Pokémon to train, so you can be as effective as possible against a wide variety of opponents. As each Pokémon has its strengths and weaknesses, we created clusters of Pokémon with similar characteristics and looked at the few selected ones allowing the player to compete against as many different enemies as possible.
For our latest blog, we took discussion comments from the Slovak sports community website sport.sk and fed them to our deep learning model. We wanted to see, whether we could teach a model to generate these comments automatically from all the past comments we had and if it was going to learn the structures and nuances used in them. Enjoy! (Article is both in Slovak and English).
It always gives us great pleasure to see, when one of our clients gets recognition for the great work they are doing. It is even better, if they are enabling people from developing countries to do things, which were not possible only a little while ago. This is exactly what FinAccel is doing.
Next week, Lukas is going to give last two from his lectures series on data science. First, on Tuesday, he will visit Matej Bel University in Banska Bystrica, Slovakia, from where he will move to Prague, on Thursday, this time to present data science to students of Institute of Economic Studies (Charles University).
Everyone keeps talking about data; its great value, utility, and the many benefits it offers. However, to many people all those might just seem like abstract concepts. That's why we want to show you what data means in real life: data to help, data to increase efficiency, and sometimes data just to amuse. We point out use cases where data science helped someone to solve a unique problem or to solve a very old problem in a unique way. We will demonstrate that data can help individuals, communities, as well as corporations and governments. It's not a universal solution to everything, but it is right up there :)