US Insurance cost predicting linear regression model. Mainly used to learn about Machine Learning tools in Amazon Web Services (AWS)
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Updated
Dec 17, 2023 - Jupyter Notebook
US Insurance cost predicting linear regression model. Mainly used to learn about Machine Learning tools in Amazon Web Services (AWS)
A simple, practical, and affordable system for measuring head trauma within the sports environment, subject to the absence of trained medical personnel made using Amazon Kinesis Data Streams, Kinesis Data Analytics, Kinesis Data Firehose, and AWS Lambda
Scrapped tweets using twitter API (for keyword ‘Netflix’) on an AWS EC2 instance, ingested data into S3 via kinesis firehose. Used Spark ML on databricks to build a pipeline for sentiment classification model and Athena & QuickSight to build a dashboard
A data pipeline to ingest, process, store storm events datasets so we can access them through different means.
Build a Visualization and Monitoring Dashboard for IoT Data with Amazon Kinesis Analytics and Amazon QuickSight
AWS Programming and Tools meetup workshop
Streaming data pipeline on aws, Tech session repository for hist
ML Model that takes a user's resume and desired job's profile, identifies skills gaps and recommends course learning pathway to bridge gap
An End-To-End data pipeline integration from Website Source to analytical dashboard in AWS using Python flask, ML models, DynamoDB and other AWS services.
Unveiling job market trends with Scrapy and AWS
This project aims to securely manage, streamline, and perform analysis on the structured and semi-structured YouTube videos data based on the video categories and the trending metrics.
This project is based for legacy applications that works with positional files to process data. The objetive is read these positional files when they arrives in AWS S3, and then send to a dataware-house like AWS Redshift, and finally read the results with a Business Intelligence tool as AWS QuickSight.
Put-away is one of the most crucial process in supply chain. If we misplace the goods, all of the rest process could be potentially delayed. That's why we choose this process to be improved by multiclassification machine learning model and dashboarding with AWS.
Data Engineering Final Project - June 23, 2022
Get the dataset intro a S3 bucket, use AWS glue to transform the dataset, write a Lambda script to clean the dataset, query the dataset via AWS Athena then build a dashboard using AWS Quicksight.
. The specific project covered in the tutorial involves using Amazon S3 and Amazon QuickSight to create visualizations from a data set of 50,000 best-selling products on Amazon.com provided by Bright Data.
This project repo 📺 offers a robust solution meticulously crafted to efficiently manage, process, and analyze YouTube video data leveraging the power of AWS services. Whether you're diving into structured statistics or exploring the nuances of trending key metrics, this pipeline is engineered to handle it all with finesse.
The testbed showing how to embed QuickSight dashboards into a web app
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