The area of privacy preserving machine learning has been of growing importance in practice, which has lead to an increased interest in this topic in both academia and industry. We have witnessed this through numerous papers and systems published and developed in the recent years to address challenges in this area. The solutions proposed in this space leverage many different approaches and techniques coming from machine learning, cryptography, and security. Thus, the workshop aims to be a forum to unify different perspectives and start a discussion about the relative merits of each approach. It will also serve as a venue for networking people from different communities interested in this problem, and hopefully foster fruitful long-term collaboration.