Category: Artificial Intelligence

Update Sept. 28, 2023 – Amazon Sumerian is no longer available. This guest post is by AWS Machine Learning Hero, Cyrus Wong. Cyrus is a Data Scientist at the Hong Kong Institute of Vocational Education (Lee Wai Lee) Cloud Innovation Centre. He has achieved all nine AWS Certifications and enjoys sharing his AWS knowledge with […]

Join us in the next couple weeks to learn about some of the new service and feature launches from re:Invent 2018. Learn about features and benefits, watch live demos and ask questions! We’ll have AWS experts online to answer any questions you may have. Register today! Note – All sessions are free and in Pacific […]

Machine learning (ML) is split in two distinct phases: training and inference. Training deals with building the model, i.e. running a ML algorithm on a dataset in order to identify meaningful patterns. This often requires large amounts of storage and computing power, making the cloud a natural place to train ML jobs with services such […]

The capacity to foresee the future would be an incredible superpower. At AWS, we can’t give you that, but we can help you use machine learning to forecast time series in a few steps. The goal of time series forecasting is to predict future values of time-dependent data such as weekly sales, daily inventory levels, […]

Machine learning definitely offers a wide range of exciting topics to work on, but there’s nothing quite like personalization and recommendation. At first glance, matching users to items that they may like sounds like a simple problem. However, the task of developing an efficient recommender system is challenging. Years ago, Netflix even ran a movie […]

In the last few years, machine learning (ML) has generated a lot of excitement. Indeed, from medical image analysis to self-driving trucks, the list of complex tasks that ML models can successfully accomplish keeps growing, but what makes these models so smart? In a nutshell, you can train a model in several different ways of which […]

In 1959, Arthur Samuel defined machine learning as a “field of study that gives computers the ability to learn without being explicitly programmed”. However, there is no deus ex machina: the learning process requires an algorithm (“how to learn”) and a training dataset (“what to learn from”). Today, most machine learning tasks use a technique […]

One of the reasons for the recent progress of Artificial Intelligence and Deep Learning is the fantastic computing capabilities of Graphics Processing Units (GPU). About ten years ago, researchers learned how to harness their massive hardware parallelism for Machine Learning and High Performance Computing: curious minds will enjoy the seminal paper (PDF) published in 2009 […]