When we first launched the Datascience.aero blog in 2017, we hoped to regularly update our readers on the evolution of data science based solutions as applied to the aviation industry. We presented these updates alongside other breakthrough ideas that might inspire others with new applications. Following this spirit, we have continued to publish our thoughts [...]
Artificial intelligence bot applications have become very popular recently, not only within the data science and machine learning communities, but across unrelated industries that have found creative uses for its application. This kind of AI opens a whole new world of possibilities, and may imply a potential threat to some jobs, such as artists or […]
“Please allow me to introduce myself…” These are the words to the opening track of a 1968 well-known rock song. Now, imagine the current Air Traffic Management System (ATM) needed to introduce itself. How do you envision the ATM system today? Do you see it as a 1920s telephone switchboard operator connecting plugs into the communication jacks, or perhaps a […]
Machine learning allows us to automatically learn hidden patterns in the data. Traditionally, machine learning models are classified as supervised learning, unsupervised learning and reinforcement learning. In this article, we focus on the synergy between the first two paradigms: Supervised learning. The objective is to find functions that establish a correspondence between inputs and target outputs when given […]
In February 2020, the European Commission published a manuscript providing an overview of the objectives sought in Europe related to digital transformation. The text mentions that the ICT sector is responsible for between 5% and 9% of global electricity consumption and 2% of all emissions. With the current trend of increased digitalisation it is expected that these […]
What are topic models and why is their interpretability important? Topic modelling algorithms, such as Latent Dirichlet Allocation (LDA) which we used in the H2020-funded coordination and support action CAMERA, are a set of natural language processing (NLP) based models used to detect underlying topics in huge corpora of text. However, the interpretability of the topics [...]
Natural Language Processing techniques can be used for a wide range of applications based on several capabilities: Information retrieval: finding relevant material within document (textual) repositories that fulfills a certain condition. Sentiment analysis: understanding the subjective component of the contextm underlying sentiments or categorizing opinions, comments or feedback. Machine translation: translating texts from one language [...]
Natural Language Processing (NLP) is a fast evolving branch of AI, which focuses on analysis and understanding of human languages. NLP is experiencing an incremental growth parallel with the development of better and more understandable Deep Learning models. But as with every other technology labeled as "Artificial Intelligence", NLP is helping computers develop language understanding [...]
The data science team at Innaxis attended the Big Data Spain 2018 conference to learn about the latest development in data processing and improve our data processing skills. It is the biggest Big Data event hosted in Spain and with almost 100 speakers participating in 80 different talks. Although the conference is mainly ICT, many […]
Now that the ultra-hype period has passed, I think it is time to talk about Google Duplex. If you haven't heard about it, there is a great post on the Google AI blog, or you can watch the following video. At first it might seem scary, then it might feel exciting. Are we actually approaching an [...]