Summary — #522: Data Sci Tips and Tricks from CodeCut.ai
Host: Michael Kennedy
Guest: Rajiv Shah (Chief Evangelist, Contextual AI)
Note: The provided transcript is an introductory fragment; the main interview content (actual data-science tips/tricks) is not included.
Overview
This transcript covers the podcast introduction and brief host/guest greetings. Michael Kennedy introduces Rajiv Shah as a returning guest and contextual AI evangelist, mentions that Chris is absent for this episode, and plugs the upcoming Midwest AI Summit (Nov 13, Indianapolis). Much of the excerpt is repetition of the guest greeting, so substantive discussion is missing from the provided text.
Key points & main takeaways
- Episode features Rajiv Shah from Contextual AI as the guest; he is a recurring contributor to the show.
- The hosts will be attending and promoting the Midwest AI Summit on November 13 in Indianapolis.
- Listeners are encouraged to connect with the podcast on social platforms (LinkedIn, X, BlueSky).
- The transcript supplied is incomplete and contains mostly intro/repetition rather than the promised data science tips.
Notable quotes / insights
- “Be sure to connect with us on LinkedIn, X or Blue Sky to stay up to date with episode[s].”
- “If you live anywhere near corn and you like AI, then this is the place to be.” — lighthearted plug for the Midwest AI Summit.
- Repeated: “It’s great to be here.” (guest greeting repeated many times in the fragment)
Topics discussed (from this fragment)
- Episode and guest introductions
- Promotional mention of the Midwest AI Summit (date & location)
- Social media call-to-action for listeners
Action items / recommendations
- If you want the actionable data-science tips implied by the episode title, listen to the full episode (this transcript is only the intro).
- Connect with the Practical AI Podcast and Rajiv Shah on LinkedIn/X/BlueSky to follow episode updates and related resources.
- Consider attending the Midwest AI Summit (Nov 13, Indianapolis) if local and interested in AI.
- If you need a complete summary of the episode’s technical content, provide the full transcript or the rest of the audio and I will produce a focused summary of the tips/tricks discussed.
Notes / Caveats
- The transcript provided is heavily truncated/repetitive and lacks the substantive interview content. The above summary reflects only what is present in the fragment.
