Workshop to build voice enabled integration with data analytics
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Updated
Mar 13, 2020 - Python
Workshop to build voice enabled integration with data analytics
The Discovering Hot Topics Using Machine Learning solution helps brand-conscious customers understand the most popular topics being actively discussed by ingesting digital assets and performing near real-time inferences and analytics
QuickSight artifacts with CDK, CodePipeline, CLI scripts
Terraform module for creating Cost and Usage Reports complete with Glue and Athena to make CUR data available to e.g. QuickSight.
Data Engineering pipeline hosted entirely in the AWS ecosystem utilizing DocumentDB as the database
An AWS Data Engineering End-to-End Project (Glue, Lambda, Kinesis, Redshift, QuickSight, Athena, EC2, S3)
This is a solution that demonstrates how to train and deploy a pre-trained Huggingface model on AWS SageMaker and publish an AWS QuickSight Dashboard that visualizes the model performance over the validation dataset and Exploratory Data Analysis for the pre-processed training dataset.
Example how to Analyze DynamoDB data with Athena in different ways created with AWS CDK
aws-quicksight-tool assists in the use of the AWS QuickSight CLI.
Building and executing end-to-end ELT pipeline and driving analytics using Amazon Redshift as the data warehouse solution.
This Repository Contains Detailed Explanation of AWS QuickSight's Latest feature( Augmenting QuickSight WIth SageMaker) . It Also Contains Deploying your own models in SageMaker AWS.
AWS Serverless Analytics using Amazon S3, Athena, Glue, and QuickSight
This solution ingests flat files into AWS IoT Core using AWS IoT Greengrass at the edge. The data is then stored and analyzed using AWS IoT Analytics and visualized using Amazon QuickSight.
End-to-end simple data analysis in AWS
(@czhc) Updated 2019 AWS summit workshop content
Event-Driven Python on AWS #CloudGuruChallenge
Inventory Visualization for countries and sites with control for deep diving
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