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When & Where
Schedule: 
Alternating Fridays, 12:30-2:00pm, first meeting on Friday September 8
Location: 
Barrows 356: Convening Room
Description

Are you new to machine learning but do not know how to get started? Do you have experience with machine learning and are looking for a venue to practice presenting your research? If you answered yes to either of these questions, then come join the UC Berkeley Social Sciences Data Laboratory (D-Lab) Machine Learning Working Group! 

This brown-bag series will introduce you to central themes in the form of short lectures and topic discussions. Coding walkthroughs will be demonstrated using R and Python. The topic for Fall semester 2017 will be neural networks! We will focus on key frameworks in R such as caret and SuperLearner and in Python like scikit-learn, tensorflow, theano, and keras. 

We also encourage you to bring topics for discussion that focus on a variety of themes including algorithm creation, data cleaning, visualization, automation, cloud computing, and parallel processing. 

Prior knowledge: R FUN!damentals: Parts 1 through 3 or previous intermediate working knowledge of R or Python FUN!damentals and previous work with NumPy and SciPy.

 

Details
D-lab Facilitator: 
Evan Muzzall