Fundamentals of Machine Learning Workshop at Stanford University
March 31, 2017
Discover the basics behind the application of modern machine learning algorithms. The workshop instructors will discuss a framework for reasoning about when to apply various machine learning techniques, emphasizing questions of over-fitting/under-fitting, regularization, interpretability, supervised/unsupervised methods, and handling of missing data.
For more information, visit the Stanford ICME website: https://icme.stanford.edu/events/fundamentals-machine-learning-workshop
Attendees should have undergraduate-level knowledge of linear algebra and statistics, and basic programming experience (R/Matlab/Python). Please note that this is not a Stanford for-credit course.
Space is limited, so register today.
Thanks to Judy Logan from the Institute for Computational and Mathematical Engineering (ICME) at Stanford University and the Women in Data Science (WiDS) Conference for this post.
bigmathnetwork.org 
What was the community favorite? I lean toward R for projects, but I know Python seems to perform better with image recognition as of now.
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