Explains data annotation, its importance for training machine learning models, and details common text and image annotation types.
A tutorial on building a no-code incident management system using Azure Logic Apps to monitor Twitter sentiment and create PagerDuty alerts.
A technical guide on building a serverless app to collect and store Twitter data for stock sentiment analysis using AWS Lambda and DynamoDB.
A technical guide on building a serverless app using AWS Lambda and Comprehend to analyze sentiment from tweets about companies.
A developer built an interactive tool using the DEV API to analyze article readability and sentiment over time, visualizing the data with charts.
Analyzing tweet sentiment towards public figures using R, word embeddings, and logistic regression models to measure online negativity.
A deep dive into AWS S3 Batch Operations, covering its core elements and providing a walkthrough for running a batch job with Lambda and Comprehend.
A tutorial replicating a Python experiment on creating a biased AI sentiment classifier, but using R, GloVe embeddings, and glmnet for logistic regression.
A technical analysis using sentiment analysis on Warren Buffett's shareholder letters from 1977-2016 to identify trends in tone and market influence.
Technical guide on building a real-time Twitter sentiment analysis system using Apache Kafka and Storm.
A technical guide on building a real-time Twitter sentiment and hashtag analysis system using Kafka, Storm, and Cassandra.
A tutorial on building an Outlook add-in that uses Azure Text Analytics to classify email sentiment as positive, neutral, or negative.
