Bias is, unfortunately, a reality of machine learning. While it cannot be completely banished from AI processes, there are several measures that can be adopted to reduce it and diminish its effects.

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

AI and ML projects will fail without good data because data is the foundation that enables these technologies to learn. Data strategies and AI and ML strategies are intertwined. Enterprises must make ...

Based on data, machine learning can quickly and efficiently analyze large amounts of information to provide suggestions and help make decisions. For example, phones and computers expose us to ...

It is important to recognize the limitations of our data, models, and technical solutions to bias, both for awareness’ sake, and so that human methods of limiting bias in machine learning such ...

Machine learning models often struggle to make accurate predictions for individuals underrepresented in their training datasets. For example, a model trained predominantly on data from male ...

Quality data is at the heart of the success of enterprise artificial intelligence (AI). And accordingly, it remains the main source of challenges for companies that want to apply machine learning ...

Machine learning is a powerful tool for the modern enterprise. It offers insights that extend far beyond business intelligence and data analytics. Written by eWEEK content and product ...

Data poisoning is a type of adversarial ML attack that maliciously tampers with datasets to mislead or confuse the model. The goal is to make it respond inaccurately or behave in unintended ways.

By 2030, it’s expected that the market for streaming data will eclipse $73 billion, growing nearly 20% each year until then. More impressively, the machine learning market—which brought in $15 ...

Rice researchers found two machine learning models widely used for immunotherapy research did not correct for bias present in the publicly available data used to train the models, which appears to ...