Simple models are much easier to implement today since they’re more accessible.

The first key to a successful machine learning project is an ability to collect, store and quickly access large volumes of data. More data means more side cases and more nuanced and precise models.

It may be the buzziest tech trend of the moment, but machine learning is no easy matter. Before you jump into writing machine learning algorithms, here are the basics you need to start a project.

TensorFlow is a Python-friendly open source library for developing machine learning applications and neural networks. Here's what you need to know about TensorFlow.

In flipped learning, students acquaint themselves with new content and practice skills ahead of class via activities developed by their teacher and posted online. When class convenes, time that once ...

A simple electric circuit learns to classify data in a creative new design that could lead to more energy-efficient machine-learning hardware.

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.

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 ...

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.