In this article, the author discusses a machine learning pipeline with observability built-in for credit card fraud detection use case, with tools like MLflow, FastAPI, Streamlit, Apache Kafka ...

The increasing digitalization of banking services has led to a surge in financial fraud, necessitating advanced detection systems. Financial institutions worldwide reported over $485 billion in ...

Normally anomaly detection takes time to set up. You need to train your model against a large amount of data to determine what’s normal operation and what’s out of the ordinary.

As a result, NLP greatly extends the capabilities and effectiveness of machine learning. The Deepfake Challenge Then, there is the “most entertaining” fraud of them all: deepfakes.

Cybercrime is big business and hackers are continually looking for new attack vectors. SophosLabs team see 400,000 new malicious samples every day; this does not mean 400,000 programmers writing code.

Machine learning is a powerful tool for identifying and interpreting patterns and anomalies in data. Machine learning can boost business growth by streamlining inventory management, identifying more ...

Facebook is now releasing details about the machine-learning system it uses to tackle… Fraudsters use fake accounts to spread spam, phishing links, or malware. Now Facebook is revealing details ...

In February, OpenAI released videos created by its generative artificial intelligence program Sora. The strikingly realistic content, produced via simple text prompts, is the latest breakthrough for ...