Chapter 5: Machine Learning Basics Part 1
Details
Since Chapter 5 is very long we will be splitting it into 2 parts.
During this session we will discuss sections 1-6 (Learning Algorithms through Bayesian Statistics).
We are very fortunate to have Jeremy Howard present this time. Jeremy was the President and Chief Scientist at Kaggle (https://en.wikipedia.org/wiki/Kaggle). He taught at Singularity University and is an author of Deep Learning MOOK. You can read more about him here: https://en.wikipedia.org/wiki/Jeremy_Howard_(entrepreneur )
Jeremy is a fantastic teacher and I am just so very excited!
Additional resource per Cosmin Negruseri (https://www.meetup.com/Deep-Learning-Book-Club/members/182630293/), who found this video from last year's Montreal Deep Learning summer school, which covers quite a bit of ground and overlaps with the topics mentioned in the book: http://videolectures.net/deeplearning2016_precup_machine_learning/ (http://videolectures.net/deeplearning2016_precup_machine_learning/)
Everyone should read the chapter beforehand and bring a personal copy to the meetup. You must RSVP to attend due to campus security.