The importance of data quality & profiling for the success of Machine Learning In today's world, businesses around the globe are generating a vast amount of data. To be able to adopt a data-driven initiative, organizations must manage data...
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In the dynamic landscape of Data-Centric AI, data quality is crucial for the success of any analytics or machine learning initiative. Data profiling is an essential process that provides insights into the intricacies of your datasets,...
Synthetic data is a cornerstone of Data Centric-AI, an approach that focuses primarily on data quality rather than models. For the past few years, synthetic data gained attention because of a wide range of applications such as data...
In recent years, machine learning has revolutionized how businesses and organizations operate. However, one aspect that is often overlooked is the importance of data pipelines in influencing machine learning performance. In this paper, the...
Predicting air quality is a complex task that has become increasingly relevant in urban areas due to air pollution's critical impact on human health and the environment. In this context, machine learning techniques have proven to be...