Materials

## Materials Materials such as slides or other notes from lectures will be posted here, typically on the day of the lecture or by the end of that day. ### Deepak Agarwal ### Xavier Amatriain ### Anima Anandkumar ### Dan Feldman ### Nando de Freitas

• Lecture 1: Bayesian optimization (video, slides)
• Lecture 2: RL and deep learning (video, slides)

Zico Kolter

• Welcome to MLSS 2014 (video, slides)
• Lecture 1: Introduction to Machine Learning (video, slides)
• Lecture 2: Introduction to Machine Learning (video, slides)

Mu Li

• Lecture 1: Parameter Server Tutorial (video)
• Lecture 2: Parameter Server Tutorial (video) Slides: Introduction, Optimization, Parameter Server, Sparse Data

Quoc Le

• Lecture 1: Deep Learning (video)
• Lecture 2: Deep Learning (video)

Tom Mitchell

Muthu Muthukrishnan

Alex Smola

• Lecture 1: Scaling Machine Learning (video) (slides slides)
• Lecture 2: Scaling Machine Learning (video)

Markus Weimer

Andrew Wilson