Category: Advanced (300)

Amazon SageMaker Automatic Model Tuning has introduced Autotune, a new feature to automatically choose hyperparameters on your behalf. This provides an accelerated and more efficient way to find hyperparameter ranges, and can provide significant optimized budget and time management for your automatic model tuning jobs. In this post, we discuss this new capability and some […]

This post is co-written with Philipp Schmid from Hugging Face. We have all heard about the progress being made in the field of large language models (LLMs) and the ever-growing number of problem sets where LLMs are providing valuable insights. Large models, when trained over massive datasets and several tasks, are also able to generalize […]

The demand for multi-object tracking (MOT) in video analysis has increased significantly in many industries, such as live sports, manufacturing, and traffic monitoring. For example, in live sports, MOT can track soccer players in real time to analyze physical performance such as real-time speed and moving distance. Since its introduction in 2021, ByteTrack remains to […]

Running machine learning (ML) workloads with containers is becoming a common practice. Containers can fully encapsulate not just your training code, but the entire dependency stack down to the hardware libraries and drivers. What you get is an ML development environment that is consistent and portable. With containers, scaling on a cluster becomes much easier. […]

PyTorch is a machine learning (ML) framework based on the Torch library, used for applications such as computer vision and natural language processing. One of the primary reasons that customers are choosing a PyTorch framework is its simplicity and the fact that it’s designed and assembled to work with Python. PyTorch supports dynamic computational graphs, […]

The Amazon SageMaker Python SDK is an open-source library for training and deploying machine learning (ML) models on Amazon SageMaker. Enterprise customers in tightly controlled industries such as healthcare and finance set up security guardrails to ensure their data is encrypted and traffic doesn’t traverse the internet. To ensure the SageMaker training and deployment of […]

Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning. They can process various types of input data, including tabular, […]

Cost optimization is one of the pillars of the AWS Well-Architected Framework, and it’s a continual process of refinement and improvement over the span of a workload’s lifecycle. It enables building and operating cost-aware systems that minimize costs, maximize return on investment, and achieve business outcomes. Amazon SageMaker is a fully managed machine learning (ML) […]

Amazon Kendra is a highly accurate and intelligent search service that enables users to search unstructured and structured data using natural language processing (NLP) and advanced search algorithms. With Amazon Kendra, you can find relevant answers to your questions quickly, without sifting through documents. However, just enabling end-users to get the answers to their queries […]

Intelligent document processing (IDP) is a technology that automates the processing of high volumes of unstructured data, including text, images, and videos. IDP offers a significant improvement over manual methods and legacy optical character recognition (OCR) systems by addressing challenges such as cost, errors, low accuracy, and limited scalability, ultimately leading to better outcomes for […]