Best of Sentiment Analysis — 2025

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   Article

   Towards Data Science·49w

   Real-Time Interactive Sentiment Analysis in Python

   The post demonstrates creating a real-time interactive sentiment analysis application using Python. It details setting up the GUI with customtkinter and dynamically visualizes sentiment through a procedurally generated smiley face using OpenCV. Pre-trained transformer models from the transformers library are used for sentiment prediction, and visual updates are processed asynchronously using thread pools to ensure smooth UI performance.

   76

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2. 2
   Article

   Collections·44w

   Building an End-to-End MLOps Pipeline for YouTube Sentiment Analysis

   A comprehensive 3-hour MLOps course teaches students to build a production-ready YouTube sentiment analysis pipeline. The curriculum covers data collection and preprocessing using Reddit sentiment data, model development with MLflow tracking on AWS, and deployment using Flask and Docker. Students learn advanced practices including DVC version control, model stacking, and CI/CD automation. The course culminates in creating a Chrome extension for real-time YouTube comment sentiment analysis, providing hands-on experience with modern ML tools and bridging the gap between theory and deployable ML solutions.

   26
3. 3
   Article

   Foojay.io·42w

   Sentiment Analysis with Java, Quarkus, LangChain4j, and Local LLMs

   A hands-on guide to building a local sentiment analysis REST API using Java, Quarkus, and LangChain4j with Ollama-managed LLMs. The tutorial demonstrates creating a privacy-focused sentiment classifier that runs entirely on your machine using the Phi-3 Mini model, eliminating the need for cloud APIs or external dependencies. It covers project setup, AI service configuration, and testing with practical examples.

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