Sebastian Raschka is the lead AI educator at GridAI. He is the author of the book "Machine Learning with PyTorch and Scikit Learn" and also a few other books that cover the fundamentals of #machinelearning and #deeplearning techniques and implementing them with Python. He is also an Assistant Professor of Statistics at the University of Wisconsin-Madison and has been actively involved in making ML more accessible to beginners through his blogs, video tutorials, tweets and of course his books. He also holds a doctorate in Computational and Quantitative Biology from Michigan State University.
Time Stamps of the Podcast
00:02:40 Entry point in AI/ML that made you interested in it
00:05:30 How did you go about learning the basics and implementation of various methods?
00:11:45 What makes Python ideal for learning Machine Learning recently?
00:21:54 What is your book about and who is this for?
00:33:55 What goes into writing a good technical book?
00:40:50 Applying ML to toy datasets vs real-world research problems
00:47:40 Choosing b/w machine learning methods & deep learning methods
00:56:22 Large models vs architecture efficient models
01:01:25 Interpretability & Explainability in AI
01:08:45 Insights for people interested in machine learning research, academia or PhD
01:14:17 Keeping up with research in deep learning
Sebastian's homepage: https://sebastianraschka.com/
His book: https://www.amazon.com/Machine-Learning-PyTorch-Scikit-Learn-scikit-learn-ebook-dp-B09NW48MR1/dp/B09NW48MR1/
Video Tutorials: @SebastianRaschka
About the Host:
Jay is a Ph.D. student at Arizona State University.
Reach out to https://www.public.asu.edu/~jgshah1/ for any queries.
Stay tuned for upcoming webinars!
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Checkout these Podcasts on YouTube: https://www.youtube.com/c/JayShahml
About the author: https://www.public.asu.edu/~jgshah1/