Topic Detection in Podcast Episodes with Python

In this blog post, the author discusses a Python project for AI Machine Learning Topic Detection using podcast audio files. The main steps involved are transcribing speech-to-text with Deepgram's API and then applying the TF-IDF (Term Frequency - Inverse Document Frequency) topic detection algorithm to identify key topics in the podcast episode. The author provides a detailed walkthrough of the Python code, including functions for removing stop words, vectorizing cleaned documents, and performing K-Means clustering to create 10 clusters of topics. The final results are written to a file called "results.txt" for further analysis.