Sustainable Development Goals

Sustainable Development Goals (SDGs) are a set of 17 global goals adopted by the United Nations General Assembly in 2015 as a universal call to action to end poverty, protect the planet and ensure that all people enjoy peace and prosperity by 2030. Data science plays a crucial role in achieving the SDGs by providing insights into the progress made towards achieving the goals, identifying areas that require attention, and measuring the impact of interventions. Data science techniques such as machine learning, natural language processing, and data visualization are used to analyze large and complex datasets to generate actionable insights that inform policy decisions and interventions. The use of big data and artificial intelligence can also help to identify patterns and trends that can inform the development of targeted interventions and policies that address the root causes of poverty, inequality, and environmental degradation.

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Data Retrieval: Data retrieval is the process of accessing and retrieving specific information from a database or data warehouse. It involves querying the data using various techniques and tools to extract the required information. Data retrieval is an ess ... Read More >>
Community Detection: Community detection is the process of identifying groups of nodes (or communities) within a network that are more densely connected to each other than to the rest of the network. In data science, community detection is used to analyze compl ... Read More >>
Continuous Integration: Continuous Integration (CI) is a software development practice where developers frequently merge their code changes into a central repository, which is then automatically built and tested. The main goal of CI is to detect and fix integratio ... Read More >>

Sustainable Development Goals

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