AWS Machine Learning Blog

Using container images to run TensorFlow models in AWS Lambda

TensorFlow 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 deployed in production to produce inferences. […]

We use the following sample document, which has both printed and handwritten content in tables.

Process documents containing handwritten tabular content using Amazon Textract and Amazon A2I

Even in this digital age where more and more companies are moving to the cloud and using machine learning (ML) or technology to improve business processes, we still see a vast number of companies reach out and ask about processing documents, especially documents with handwriting. We see employment forms, time cards, and financial applications with […]

Talkdesk and AWS: What AI and speech-to-text mean for the future of contact centers and a better customer experience

This is a guest post authored by Ben Rigby, the VP, Global Head of Product & Engineering, Artificial Intelligence and Machine Learning at Talkdesk. Talkdesk broadens contact center machine learning capabilities with AWS Contact Center Intelligence. At Talkdesk, we’re driven to reduce friction in the customer journey. Whether that’s surfacing relevant content to agents while […]

The following diagram shows our end-to-end automated MLOps pipeline

Architect and build the full machine learning lifecycle with AWS: An end-to-end Amazon SageMaker demo

In this tutorial, we will walk through the entire machine learning (ML) lifecycle and show you how to architect and build an ML use case end to end using Amazon SageMaker. Amazon SageMaker provides a rich set of capabilities that enable data scientists, machine learning engineers, and developers to prepare, build, train, and deploy ML […]

Reviewing online fraud using Amazon Fraud Detector and Amazon A2I

Each year, organizations lose tens of billions of dollars to online fraud globally. Organizations such as ecommerce companies and credit card companies use machine learning (ML) to detect online fraud. Some of the most common types of online fraud include email account compromise (personal or business), new account fraud, and non-payment or non-delivery (including card […]

How Zopa enhanced their fraud detection application using Amazon SageMaker Clarify

This post is co-authored by Jiahang Zhong, Head of Data Science at Zopa.  Zopa is a UK-based digital bank and peer to peer (P2P) lender. In 2005, Zopa launched the first ever P2P lending company to give people access to simpler, better-value loans and investments. In 2020, Zopa received a full bank license to offer […]

The blue line in the following forecasted plot represents the historical energy usage for a specific client.

Training, debugging and running time series forecasting models with the GluonTS toolkit on Amazon SageMaker

Time series forecasting is an approach to predict future data values by analyzing the patterns and trends in past observations over time. Organizations across industries require time series forecasting for a variety of use cases, including seasonal sales prediction, demand forecasting, stock price forecasting, weather forecasting, financial planning, and inventory planning. Various cutting edge algorithms […]

The following is the architecture diagram for integrating online ML inference in a telemedicine contact flow via Amazon Connect.

Applying voice classification in an Amazon Connect telemedicine contact flow

Given the rising demand for fast and effective COVID-19 detection, customers are exploring the usage of respiratory sound data, like coughing, breathing, and counting, to automatically diagnose COVID-19 based on machine learning (ML) models. University of Cambridge researchers built a COVID-19 sound application and demonstrated that a simple binary ML classifier can classify healthy and […]

The following diagram illustrates the solution architecture.

Machine learning on distributed Dask using Amazon SageMaker and AWS Fargate

As businesses around the world are embarking on building innovative solutions, we’re seeing a growing trend adopting data science workloads across various industries. Recently, we’ve seen a greater push towards reducing the friction between data engineers and data scientists. Data scientists are now enabled to run their experiments on their local machine and port to […]

Schematically, this process looks like the following diagram.

Solving numerical optimization problems like scheduling, routing, and allocation with Amazon SageMaker Processing

July 2023: This post was reviewed for accuracy. In this post, we discuss solving numerical optimization problems using the very flexible Amazon SageMaker Processing API. Optimization is the process of finding the minimum (or maximum) of a function that depends on some inputs, called design variables. This pattern is relevant to solving business-critical problems such […]