Matt Harrison is hands-down one of the most erudite yet lucid and practical experts on data science and machine learning. His insights on decision trees mirrored things I discovered but was never able to distill and operationalize in the manner Harrison has. I learned 6 months of info in just over 60 minutes from this excellent interviewer and guest. Thanks a heap...great way to start 2024!
I love Matt, perhaps one of SuperDataScience Podcast best guests! I listened to the Effective Pandas one a year ago and have been following Matt very closely, great brain!
This episode is amazing, not only because you two are great subject matter experts talking fluently about a very specific and interesting topic, but also because of all the knowledge that Matt share and I find applicable to everything data related. It is a pity I couldn't listened this episode earlier in order to win a copy of the book, but with everything Matt shared I am already a better professional. What a fantastic libreries he recommended. I will definitely check them out! Keep up rocking Jon! You are amazing!
One of the great things about using Python in a data science workflow is it's very well documented. One of the bad things about Python is that it's tough, especially for learners, to distinguish between best practices and...not so good practices. I work in DS/DE and constantly end up recommending Matt's resources to people. IMO, the workflow that Matt demonstrates is best practice. I wish everyone would adopt the dotchain approach that Matt advocates, and abandon the MATLAB-style reassignment crap that we see everywhere. Jon and Matt together are really a dynamic duo of data science. Jon's awesome at the high level big picture stuff, and Matt is great at explaining the low level. Which is not to say that they couldn't switch roles, just that the interview format works really well with the interviewee going deep and then the interviewer stepping back and summarizing.
Great video! Thanks Matt for sharing your knowledge. As a DS here in FinTech I see XGBoost used often. Great stuff here. Subscribed. Cheers from Atlanta, Ga.
My apologies - my social media team copied and pasted my LinkedIn post (where you could comment and receive a book) directly to my blog. I've advised them of this error, which is being fixed and can hopefully be avoided in the future.
Matt Harrison is hands-down one of the most erudite yet lucid and practical experts on data science and machine learning. His insights on decision trees mirrored things I discovered but was never able to distill and operationalize in the manner Harrison has. I learned 6 months of info in just over 60 minutes from this excellent interviewer and guest. Thanks a heap...great way to start 2024!
Matt Harrison is someone I respected so much in the field. Hands down he's the GOAT
He certainly is, Andreas :)
I love Matt, perhaps one of SuperDataScience Podcast best guests! I listened to the Effective Pandas one a year ago and have been following Matt very closely, great brain!
@@JR-gy1lh couldn't agree more :)
This episode is amazing, not only because you two are great subject matter experts talking fluently about a very specific and interesting topic, but also because of all the knowledge that Matt share and I find applicable to everything data related.
It is a pity I couldn't listened this episode earlier in order to win a copy of the book, but with everything Matt shared I am already a better professional. What a fantastic libreries he recommended. I will definitely check them out!
Keep up rocking Jon! You are amazing!
Cheers, Matias! Thank you for this thoughtful, encouraging feedback - delighted to have you listening :)
One of the great things about using Python in a data science workflow is it's very well documented.
One of the bad things about Python is that it's tough, especially for learners, to distinguish between best practices and...not so good practices.
I work in DS/DE and constantly end up recommending Matt's resources to people. IMO, the workflow that Matt demonstrates is best practice. I wish everyone would adopt the dotchain approach that Matt advocates, and abandon the MATLAB-style reassignment crap that we see everywhere.
Jon and Matt together are really a dynamic duo of data science. Jon's awesome at the high level big picture stuff, and Matt is great at explaining the low level. Which is not to say that they couldn't switch roles, just that the interview format works really well with the interviewee going deep and then the interviewer stepping back and summarizing.
Cheers, Marty! Very kind of you to provide this positive feedback. And I agree with you 100% on the dotchain best practice :)
Great video! Thanks Matt for sharing your knowledge. As a DS here in FinTech I see XGBoost used often. Great stuff here. Subscribed. Cheers from Atlanta, Ga.
Nice, Sonofa Brewing! Hope you're brewing up something delicious :)
Can you do one podcast on Clustering . How it's applied in industry
I am from Taiwan, and all I want to say is thank you!
I am from Canada, and all I want to say is you're welcome!
This is great!
Glad you like it, Elias!
I would like a free copy of the book please. The blog said to comment on post but can't see where.
My apologies - my social media team copied and pasted my LinkedIn post (where you could comment and receive a book) directly to my blog. I've advised them of this error, which is being fixed and can hopefully be avoided in the future.
@@JonKrohnLearns thanks for clarifying. Much appreciated.