“Adding quantum machine learning to a quantum-sensing protocol enables you to apply the method when the encoding mechanism is unknown or when hardware noise affects the quantum probe.” That ...

Researchers at IBM Quantum recently showed that simple and more accessible machine learning (ML) techniques could be used for QEM. Their paper, published in Nature Machine Intelligence ...

Using Simple ML for big data-driven projects. Although Simple ML truly is simple and focused on a less ML-savvy clientele, big data and machine learning experts alike can use this tool to manage ...

In addition, Simple ML enables users to send AI models to Colab, a cloud-based code editor developed by Google that lends itself to machine learning and data science projects. Simple ML is ...

The creative new approach could lead to more energy-efficient machine-learning hardware. On a table in his lab at the University of Pennsylvania, physicist Sam Dillavou has connected an array of ...

With how common machine learning has become today, you may wonder how it works and what its limitations are. So here’s a simple primer on the technology.

But a new paper in npj Computational Materials shows that even a simple machine learning model, trained with a modest amount of data, can significantly reduce the time needed for calculating ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

A crucial part of the machine learning lifecycle is managing data drift to ensure the model remains effective and continues to provide business value. Data is an ever-changing landscape, after all.

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes.