Category: Advanced (300)

In the world of machine learning (ML), the quality of the dataset is of significant importance to model predictability. Although more data is usually better, large datasets with a high number of features can sometimes lead to non-optimal model performance due to the curse of dimensionality. Analysts can spend a significant amount of time transforming […]

According to a PWC report, 32% of retail customers churn after one negative experience, and 73% of customers say that customer experience influences their purchase decisions. In the global retail industry, pre- and post-sales support are both important aspects of customer care. Numerous methods, including email, live chat, bots, and phone calls, are used to […]

Batch inference is a common pattern where prediction requests are batched together on input, a job runs to process those requests against a trained model, and the output includes batch prediction responses that can then be consumed by other applications or business functions. Running batch use cases in production environments requires a repeatable process for […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Businesses are increasingly using machine learning (ML) to make near-real-time decisions, such as placing an ad, assigning a driver, recommending a product, or even dynamically pricing products […]

“Instead of focusing on the code, companies should focus on developing systematic engineering practices for improving data in ways that are reliable, efficient, and systematic. In other words, companies need to move from a model-centric approach to a data-centric approach.” – Andrew Ng A data-centric AI approach involves building AI systems with quality data involving […]

RStudio on Amazon SageMaker is the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale. […]

Globally, many organizations have critical business data dispersed among various content repositories, making it difficult to access this information in a streamlined and cohesive manner. Creating a unified and secure search experience is a significant challenge for organizations because each repository contains a wide range of document formats and access control mechanisms. Amazon Kendra is […]

Enterprise customers have multiple lines of businesses (LOBs) and groups and teams within them. These customers need to balance governance, security, and compliance against the need for machine learning (ML) teams to quickly access their data science environments in a secure manner. These enterprise customers that are starting to adopt AWS, expanding their footprint on […]

You don’t have to be an expert in machine learning (ML) to appreciate the value of large language models (LLMs). Better search results, image recognition for the visually impaired, creating novel designs from text, and intelligent chatbots are just some examples of how these models are facilitating various applications and tasks. ML practitioners keep improving […]

With the advent of high-speed 5G mobile networks, enterprises are more easily positioned than ever with the opportunity to harness the convergence of telecommunications networks and the cloud. As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers […]