Favorite Training an accurate machine learning (ML) model requires many different steps, but none are potentially more important than data processing. Examples of processing steps include converting data to the input format expected by the ML algorithm, rescaling and normalizing, cleaning and tokenizing text, and many more. However, data processing
Favorite For many students, embarking on a higher education journey is an exciting time filled with new experiences. However, like anything new, it also can also bring plenty of questions to answer and obstacles to overcome. Oklahoma State University, Oklahoma City (OSU-OKC) recognized this, and was intent on providing a
Favorite PyTorch is an open-source machine learning (ML) library widely used to develop neural networks and ML models. Those models are usually trained on multiple GPU instances to speed up training, resulting in expensive training time and model sizes up to a few gigabytes. After they’re trained, these models are
Favorite Knowledge Management roles and accountabilities are one of the four legs on the KM table, but receive comparatively little attention. They seem to be a bit of a “blind spot”. In our consulting work, we find that Knowledge Management roles often do not get the same level of attention
Favorite The ability to rapidly iterate and train machine learning (ML) models is key to deriving business value from ML workloads. Because ML models often have many tunable parameters (known as hyperparameters) that can influence the model’s ability to effectively learn, data scientists often use a technique known as hyperparameter
Favorite As businesses and IT leaders look to accelerate the adoption of machine learning (ML) and artificial intelligence (AI), there is a growing need to understand how to build secure and compliant ML environments that meet enterprise requirements. One major challenge you may face is integrating ML workflows into existing
Favorite With the rapid growth of object detection techniques, several frameworks with packaged pre-trained models have been developed to provide users easy access to transfer learning. For example, GluonCV, Detectron2, and the TensorFlow Object Detection API are three popular computer vision frameworks with pre-trained models. In this post, we use
Favorite Personal protective equipment (PPE) such as face covers (face mask), hand covers (gloves), and head covers (helmet) are essential for many businesses. For example, helmets are required at construction sites for employee safety, and gloves and face masks are required in the restaurant industry for hygienic operations. In the
Favorite AWS is excited to announce the winner of the AWS DeepComposer Chartbusters Track or Treat challenge, Greg Baker. AWS DeepComposer gives developers a creative way to get started with machine learning (ML). In June 2020, we launched Chartbusters, a global competition in which developers use AWS DeepComposer to create
Favorite Machine learning (ML)-based solutions are capable of solving complex problems, from voice recognition to finding and identifying faces in video clips or photographs. Usually, these solutions use large amounts of training data, which results in a model that processes input data and produces numeric output that can be interpreted