Abstract: Accurately detecting maize leaf diseases from field images is challenging. This is because of the shortcomings of field data such as complex and non-uniform backgrounds and varying ...

Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you’ve ever built a predictive model, worked on a ...

Whether investigating an active intrusion, or just scanning for potential breaches, modern cybersecurity teams have never had more data at their disposal. Yet increasing the size and number of data ...

I would like to contribute to the synthetic liver cancer dataset (synthetic_liver_cancer_dataset.csv). This dataset is medically realistic and contains 5,000 patient records with 14 features, useful ...

(THE CONVERSATION) When business researchers analyze data, they often rely on assumptions to help make sense of what they find. But like anyone else, they can run into a whole lot of trouble if those ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...