NBDSM

What

nBDSM is the noiseBridge Deepnet and Statistical Mechanics working group. We meet weekly to learn, teach, and discuss topics at the intersection of AI/deep learning and statistical mechanics. Note that we have a non-trivial overlap with the one, the only Noisebridge DreamTeam.

We're focused on theory. Implementation is important too, but has its own set of skills that are mostly orthogonal to what we will be learning, so we will not cover it.

Prerequisites

Our discussions are usually at the level of a graduate student in machine learning or theoretical physics. To be able to get something out of our meetings, you should have at least undergrad proficiency in

• linear algebra (at the level of D. Lay's book)
• single and multi-variable calculus, and vector calculus (all of Stewart)
• statistics, including bayesian
• statistical mechanics (at the level of McGreevy's MIT lecture notes)

Links

Here are some cool links (you can use these to figure out what to study to get up to speed)

• a great talk by Ganguli at last year's deep learning summer school in Montreal.
• anything recent by Ganguli at the Neural Dynamics and Computation Lab as well.
• Calculated Content
• the venerable colah's blog