Create a comprehensive Python portfolio project by developing a smart program to download and transcribe top podcasts. Learn to scrape RSS feeds of favorite podcasters using BeautifulSoup and requests libraries, implement smart search functionality with regex and NLP libraries, and utilize AssemblyAI's speech-to-text API for podcast transcription. Explore web scraping techniques, work with MP3 files, and gain hands-on experience in natural language processing. Enhance the project by implementing functions and classes, and consider extensions like integrating the Spotify API or applying semantic search. Perfect for showcasing a wide range of Python skills, this tutorial provides step-by-step guidance on building a practical application for podcast enthusiasts and aspiring data scientists.
Overview
Syllabus
- Video Introduction
- How podcasts work RSS feeds overview
- How can we utilize the XML webpages? breakdown of RSS feed information & how we’ll use it to create a smart program
- Accessing this project on GitHub
-Writing Python code to download podcasts locally requests & beautifulsoup libraries
- Modify our script to be able to download many podcasts
- Building in smart search capabilities to grab podcasts we’ll find most interesting!
- Using the AssemblyAI API to transcribe the podcasts we’ve downloaded
- Cleaning our code with functions & classes and putting everything into Python scripts.
- Portfolio project extension ideas! Spotify API, NLP semantic search
- Smash like & subscribe pretty please :
Taught by
Keith Galli
