Category: Analytics

In this blog post, I’ll show you how to perform exploratory analysis on massive corporate data sets in Amazon SageMaker. From your Jupyter notebook running on Amazon SageMaker, you’ll identify and explore several corporate datasets in the corporate data lake that seem interesting to you. You’ll discover that each contains a subset of the information you need. You’ll join them to extract the interesting information, then continue analyzing and visualizing your data in your Amazon SageMaker notebook, in a seamless experience.

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. People spend a lot of time searching documents. First you go to your document store and then you search for relevant documents. If you’re looking for a text inside the document, then you need to do another search. In this […]

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. Yesterday we announced the integration of AWS DeepLens with […]

Today consumers are encouraged to express their satisfaction or frustration with a company or product through social media, blogs, and review platforms. Sentiment analysis can help companies better understand their customers’ opinions and needs and make more informed business decisions. Amazon released a dataset to the public with over 130 million product reviews in multiple […]

With recent advances in CPU and GPU technology, training complex and deep neural network models in a few hours is within reach for many state of-the-art deep models. However, when you use a system with such high processing throughput potential, the required data for the processing pipeline must be ready before each iteration.

In this blog post, we’ll use your webcam on your laptop to send a live feed to an Amazon Kinesis Video Stream. From there, a processor within Amazon Rekognition Video analyzes the feed and compares it to a collection we create. The output matches will get sent to us via an email through an integration with AWS Lambda and Amazon Simple Notification Service (Amazon SNS).

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. This is a guest blog post by Ned T. Sahin, PhD (Brain Power LLC and Harvard University), Runpeng Liu (Brain Power LLC and MIT), Joseph Salisbury, PhD […]

Whatever your use case, real-time face recognition with Kinesis Video Streams and Rekognition Video is easy to set up and doesn’t require expensive hardware. The entire system built here is serverless and Rekognition Video qualifies for the AWS Free Tier.

In today’s world, public content has never been more relevant. Data from customer reviews is being used as a tool to gain insight into consumption-related decisions as the understanding of its associated sentiment grants businesses invaluable market awareness and the ability to proactively address issues early. Sentiment analysis uses a process to computationally determine whether […]

In this blog post we’ll show you how you can use Amazon Translate, Amazon Comprehend, Amazon Kinesis, Amazon Athena, and Amazon QuickSight to build a natural-language-processing (NLP)-powered social media dashboard for tweets. Social media interactions between organizations and customers deepen brand awareness. These conversations are a low-cost way to acquire leads, improve website traffic, develop […]