Category: Artificial Intelligence

Though it seems like something out of a sci-fi movie, machine learning (ML) is part of our day-to-day lives. So often, in fact, that we may not always notice it. For example, social networks and mobile applications use ML to assess user patterns and interactions to deliver a more personalized experience. However, AWS services provide […]

Many organizations with large ecommerce presences have procedures to detect major anomalies in their user traffic. Often, these processes use static alerts or manual monitoring. However, the ability to detect minor anomalies in traffic patterns near real-time can be challenging. Early detection of these minor anomalies in ecommerce traffic (such as website page visits and […]

Recently, the Accenture AWS Business Group (AABG) assisted a customer in developing a secure and personalized Interactive Voice Response (IVR) contact center experience that receives and processes payments and responds to customer inquiries. Our solution uses Amazon Connect at its core to help customers efficiently engage with customer service agents. To ensure transactions are completed […]

Financial Service (FS) providers must identify patterns and signals in a customer’s financial behavior to provide deeper, up-to-the-minute, insight into their affordability and credit risk. FS providers use these insights to improve decision making and customer management capabilities. Machine learning (ML) models and algorithms play a significant role in automating, categorising, and deriving insights from […]

Federated Learning (FL) is an emerging approach to machine learning (ML) where model training data is not stored in a central location. During ML training, we typically need to access the entire training dataset on a single machine. For purposes of performance scaling, we divide the training data between multiple CPUs, multiple GPUs, or a […]

Organizations have been collecting text data for years. Text data can help you intelligently address a range of challenges, from customer experience to analytics. These mixed language, unstructured datasets can contain a wealth of information within business documents, emails, and webpages. If you’re able to process and interpret it, this information can provide insight that […]

Running machine learning (ML) inference on large datasets is a challenge faced by many companies. There are several approaches and architecture patterns to help you tackle this problem. But no single solution may deliver the desired results for efficiency and cost effectiveness. In this blog post, we will outline a few factors that can help […]

The AWS Well-Architected Framework provides you with a formal approach to compare your workloads against best practices. It also includes guidance on how to make improvements. Machine learning (ML) algorithms discover and learn patterns in data, and construct mathematical models to predict future data. These solutions can revolutionize lives through better diagnoses of diseases, environmental […]

When building a machine learning algorithm, such as a regression or classification algorithm, a common goal is to produce a generalized model. This is so that it performs well on new data that the model has not seen before. Overfitting and underfitting are two fundamental causes of poor performance for machine learning models. A model […]

The AWS Architecture Center provides new and notable reference architecture diagrams, vetted architecture solutions, AWS Well-Architected best practices, whitepapers, and more. This blog post features some of our best picks from the new and newly updated content we released in the past month. 1. AWS Best Practices for DDoS Resiliency Prioritizing the availability and responsiveness […]