In this class we will present the basic principles of stochastic gradient descent. We will show how to apply it on matrix factorization, a basic ingredient for recommendation systems. Stochastic Gradient Descent is an extremely useful tool for big data analysis. Examples will be shown on python.
You are advised to download the class virtual machine and work from there. Windows users tend to have problems with python and basically every tool beingex used for machine learning. Please download the virtual machine before the beginning of the class. It is a few gigabytes and it will take too long to download and install it here.
PS: We are preparing a big hadoop cluster. Next course will be about parallel machine learning
Webex link https://meetings.webex.com/collabs/#/meetings/detail?uuid=MAVE3FL5BB2A0JLG422LUGMLSI-61RD