![]() My First Pass: Manually Scanning Show Notes If you’re neither, then I clearly did not nail the SEO or demographic for this post - thus the reason I need help -). My guess is if you got this far you’re either 1) an engineer of some sort or 2) a podcaster that wants to figure out how to create SEO rich episodes to get discovered. Manual Methods vs Machine Learning to Help Find Podcast Topics With Troy’s help, I settled on using Amazon Web Services Transcribe and Monkey Learn Text Extractor to extract keywords for individual episodes as well as all episodes combined. His post on a simplified view of the AL/ML stack is a must-read on this and helped me figure out the what and how the heck I could do this. Troy launched Productive AI (along with a podcast) to help people like me figure out how to make AI (and Machine Learning) into a productive tool. In fact, there are so many different types of platforms and services that I had to enlist my friend Troy to educate me. Going Down the Machine Learning Rabbit HoleĪ lot has changed in Machine Learning (ML) since 1999. That’s why I dusted off my python skills and jumped into the deep end of Machine Learning. ![]() Ideally, I wanted an automated way to look at all 30 to see the trends in keywords along with where in the episode those keywords were talked about. I did look at the show notes but those are incomplete and based on my faulty memory. The good news is that I do have a rough idea of podcast topics that are interesting but I did not want to listen to all the episodes again. I want to improve my site’s SEO to get more listeners.I wanted an easy way to repurpose the interviews into smaller ones based on what topics people might be interested in.They are all entrepreneurs and my target demographic.So I decided to try and figure out what podcast topics I should cover on the podcast by doing an analysis of the first 30 guests. but who knows if anyone wants to listen to that. Sure, there are standard topics like the traits, values, beliefs, skills, life journey, mindset, etc. I’m sure it might seem obvious what a podcast about my book, The Entrepreneur Ethos, should be about but it’s actually hard to figure out what topics to cover. ![]() That’s what got me thinking about a nagging problem I have related to my podcast, The Entrepreneur Ethos, how to come up with podcast topics? Podcast Topics Are Hard to Figure Out That company is long gone (it folded back in 1999) but the types of tasks our chips could do you can now do cheaply on the web. Early in my career, I worked at a semiconductor company that built neural network chips to solve problems like image compression, character recognition, face recognition, etc. I did the same kinda thing when I created the Podcast Market Fit survey.Īnother topic I have always been interested in is how computers can learn to do said mundane tasks. I’m one of those people who would rather write a script for half a day to automate some manual tasks that would only take me 30 minutes. I have always been interested in automating mundane tasks.
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