I am working my way through the Udemy data science course “Machine Learning A-Z” by Kirill Eremenko and Hadelin de Ponteves. The course steps through key machine learning algorithms and approaches using Python and R. As an R programmer, it’s great to compare to the Python code and learn it’s syntax. From my nascent observations, it takes fewer lines to code an approach with R compared to Python.
Kirill and Hadelin are clear communicators. They break-down complex information, guiding the viewer with palatable bite-sized chucks of information. I was so impressed that I sent Kirill a thank you on Udemy. Kirill responded, we added each other on LinkedIn, then he invited me as a guest on his podcast at Super DataScience!
My episode can be found here, here and here. Three links, same episode - Woo!
Thanks to Kirill for having me as a guest and giving me an excuse to talk about neuroscience – something I haven’t done for the past three years. The dorsal lateral prefrontal cortex got a mention :)
Hi Muhsin! In the podcast episode you mention that you're trying to use Topic Modeling. I'm really interested in how that is going for you. I am just now getting into such unstructured data from our customers and would love any insights into how you'd recommend I go about analyzing the massive amount of data we have from customer comments. Thanks Muhsin!
ReplyDeleteHello! That was some time ago and it didn't go well at all! I was unsatisfied with how the topic modelling categorised the comments. We subsequently engaged with vendors who had a team of NLP experts and machine learning algorithms. They claimed they could accurately create categories, though I don't think that project has commenced.
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