Category: Amazon SageMaker

November 2022: This post is now obsolete. Please refer to the latest blog post Easy and accurate forecasting with AutoGluon-TimeSeries. Whether you’re allocating resources more efficiently for web traffic, forecasting patient demand for staffing needs, or anticipating sales of a company’s products, forecasting is an essential tool across many businesses. One particular use case, known […]

The last few years have seen rapid development in the field of natural language processing (NLP). While hardware has improved, such as with the latest generation of accelerators from NVIDIA and Amazon, advanced machine learning (ML) practitioners still regularly run into issues scaling their large language models across multiple GPU’s. In this blog post, we […]

Ambarella builds computer vision SoCs (system on chips) based on a very efficient AI chip architecture and CVflow that provides the Deep Neural Network (DNN) processing required for edge inferencing use cases like intelligent home monitoring and smart surveillance cameras. Developers convert models trained with frameworks (such as TensorFlow or MXNET) to Ambarella CVflow format […]

Deploying and managing machine learning (ML) models at the edge requires a different set of tools and skillsets as compared to the cloud. This is primarily due to the hardware, software, and networking restrictions at the edge sites. This makes deploying and managing these models more complex. An increasing number of applications, such as industrial […]

This is a guest post by Kustomer’s Senior Software & Machine Learning Engineer, Ian Lantzy, and AWS team Umesh Kalaspurkar, Prasad Shetty, and Jonathan Greifenberger. In Kustomer’s own words, “Kustomer is the omnichannel SaaS CRM platform reimagining enterprise customer service to deliver standout experiences. Built with intelligent automation, we scale to meet the needs of […]

Amazon SageMaker is a managed service that makes it easy to build, train, and deploy machine learning (ML) models. Data scientists use SageMaker training jobs to easily train ML models; you don’t have to worry about managing compute resources, and you pay only for the actual training time. Data ingestion is an integral part of […]

Time series data is widely present in our lives. Stock prices, house prices, weather information, and sales data captured over time are just a few examples. As businesses increasingly look for new ways to gain meaningful insights from time-series data, the ability to visualize data and apply desired transformations are fundamental steps. However, time-series data […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Amazon SageMaker Autopilot makes it possible for organizations to quickly build and deploy an end-to-end machine learning (ML) model and inference pipeline with just a few lines of code or even without […]

Many of our AWS customers provide research, analytics, and business intelligence as a service. This type of research and business intelligence enables their end customers to stay ahead of markets and competitors, identify growth opportunities, and address issues proactively. For example, some of our financial services sector customers do research for equities, hedge funds, and […]

August 2023: This post was reviewed for accuracy. Amazon SageMaker Data Wrangler is a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and […]