Malware is evolving to evade sandboxes by pretending to be a real human behind the keyboard. The Picus Red Report 2026 shows 80% of top attacker techniques now focus on evasion and persistence, ...

AI tools are frequently used in data visualization — this article describes how they can make data preparation more efficient ...

Abstract: real-world IoT data analysis tasks, such as clustering and anomaly event detection, are unsupervised and highly susceptible to the presence of outliers. In addition to sporadic scattered ...

We ventured into dangerous waters for some underwater metal detecting, but what we didn’t expect was to be surrounded by crocodiles and a massive python. This video takes you into the wild, where we ...

Abstract: Most existing outlier detection methods rely on a single and fine-grained data representation, making them vulnerable to noise and inefficient in capturing local anomalies. Granular-ball ...

Step 1 I got a students dataset from Kaggle and imported it into Jupyter. Then I verified the data by checking .shape, .info(), and .head() to confirm rows, columns, and sample records. Step 2 I ...

PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as Outlier Detection or Anomaly ...

Editorial Note: Talk Android may contain affiliate links on some articles. If you make a purchase through these links, we will earn a commission at no extra cost to you. Learn more. As speed checks ...

ABSTRACT: In recent decades, the impact of climate change on natural resources has increased. However, the main challenges associated with the collection of meteorological data include the presence of ...