Real-Time TV Content and Commercial Break Classifier

Local Reach aims to enhance viewer experience and optimize advertising strategies by developing an algorithm capable of real-time classification of TV content and commercial breaks. The project involves creating a machine learning model that can accurately distinguish between TV shows, movies, news segments, and commercial advertisements as they are broadcasted. This will help in dynamically adjusting content delivery and ad placements, ensuring that viewers receive a seamless experience while advertisers can target their audience more effectively. The project will require the team to gather and preprocess relevant data, train and validate the model, and integrate the algorithm into a real-time processing system. Key tasks include: - Data collection and preprocessing from various TV channels. - Development and training of a machine learning model for classification. - Validation and testing of the model's accuracy and performance. - Integration of the algorithm into a real-time processing framework.