Published Paper Details:

The television industry is a constantly evolving multi-billion dollar industry. With online streaming services such as Netflix and Amazon Prime, people have access to thousands of TV shows. The rating and reviews that the audience provides is the biggest indication of whether the show is successful or not. With such data available, we can find out what features the most successful shows have in common and the shows of which genre are likely to be more successful with the help of various Machine Learning techniques such as classification and clustering. Algorithms such as k-NN, SVM, Naive Bayes, Decision Trees and Gradient Descent can be employed to build a model with high accuracy. With the worded reviews provided by the audience, we can also perform sentiment analysis using natural language processing to find out what the audience thinks about any particular show. Based on the predictions made by the model we can also make favourable recommendations to different demographics based on their interests.