15 posts found
AI tools for research and a new way to use language models
AI systems designed to assist us from the first dives to the final bibliography.
One of the missions of contemporary artificial intelligence is to help us find, sort and digest information, especially with the help of large language models. These systems have come at a time when we most need to mana…
Data Mesh and Data Fabric: New Perspectives in Enterprise Data Architectures
Over the last decade, the amount of data that organisations generate and need to manage has grown exponentially. With the rise of the cloud, Internet of Things (IoT), edge computing and artificial intelligence (AI), enterprises face the challenge of integrating and governing data from multiple sourc…
Open source auto machine learning tools
The increasing complexity of machine learning models and the need to optimise their performance has been driving the development of AutoML (Automated Machine Learning) for years. This discipline seeks to automate key tasks in the model development lifecycle, such as algorithm selection, data process…
Re3gistry: facilitating the semantic interoperability of data
The INSPIRE (Infrastructure for Spatial Information in Europe) Directive sets out the general rules for the establishment of an Infrastructure for Spatial Information in the European Community based on the Infrastructures of the Member States. Adopted by the European Parliament a…
MAMD Methodology: The Alarcos Model of Data Improvement
There is such a close relationship between data management, data quality management and data governance that the terms are often used interchangeably or confused. However, there are important nuances.
The overall objective of data management is to ensure that data meets the business requirements tha…
Vinalod: The tool to make open datasets more accessible
Public administration is working to ensure access to open data, in order to empowering citizens in their right to information. Aligned with this objective, the European open data portal (data.europa.eu) references a large volume of data on a variety of topics.
However, although the data belong to di…
Free tools to work on data quality issues
Ensuring data quality is an essential task for any open data initiative. Before publication, datasets need to be validated to check that they are free of errors, duplication, etc. In this way, their potential for re-use will grow.
Data quality is conditioned by many aspects. In this sense, the Aport…
When to use each programming language in data science?
Python, R, SQL, JavaScript, C++, HTML... Nowadays we can find a multitude of programming languages that allow us to develop software programmes, applications, web pages, etc. Each one has unique characteristics that differentiate it from the rest and make it more appropriate for certain tasks. But h…
10 Popular natural language processing libraries
The advance of supercomputing and data analytics in fields as diverse as social networks or customer service is encouraging a part of artificial intelligence (AI) to focus on developing algorithms capable of processing and generating natural language.
To be able to carry out this task in the current…
10 Popular Data Analytics and Machine Learning Libraries
Programming libraries refer to the sets of code files that have been created to develop software in a simple way . Thanks to them, developers can avoid code duplication and minimize errors with greater agility and lower cost. There are many bookstores, focused on different activities. A few weeks ag…
