In this post, we will develop a website that integrates sentiment analysis techniques and a Large Language Model to provide a comprehensive understanding of YouTube comments, enabling users to extract meaningful information effortlessly.
In this post, we will develop a website that integrates sentiment analysis techniques and a Large Language Model to provide a comprehensive understanding of YouTube comments, enabling users to extract meaningful information effortlessly.
In the fourth and final part of the article, we will perform some analytical queries on the MySQL database and create a dashboard using Streamlit.
In the third part of the article, we will demonstrate how to ingest and process transactional data using Kafka and Spark Streaming.
In the second part of the article, we will walk through the design and implementation of OLTP and OLAP databases using Cassandra and MySQL respectively.
In the first part of the article, we will discuss the overview of the project and how to set up the environment using Docker Compose.
This article explains how to set up a workflow using Apache Airflow to retrieve trending videos data from YouTube Data API v3 and store them in BigQuery.
End-to-end machine learning project on sentiment analysis. In this post, we will explore some use cases of Twitter sentiment analysis in the field of business and social science.
A practical demonstration on building a streaming analytics pipeline for warehouse inventory management on Google Cloud Platform
A detailed documentation on building a modern data warehouse in BigQuery featuring storage and performance optimization