With the advancement of Machine Learning, software applications can now learn from Big Data efficiently and perform all kinds of intelligent tasks. One of the biggest challenges for developers in building real world predictive applications is the steep learning curve of mastering multiple data-processing frameworks, algorithms and scalable systems.
This talk will begin with an overview of how Machine Learning, and user preference prediction in particular, is empowering modern web, mobile and Internet of Things in many aspects. Simon will then introduce the latest PredictionIO (http://prediction.io/) open-source Machine Learning Server and explain its design architecture. With live sample codes, Simon will demonstrate how developers can use PredictionIO to add predictive features such as personalization, recommendation and content discovery to an application. By the end of the talk, you will have mastered the whole process of predictive modeling, and will be able to apply scalable algorithms to a real software production environment.


* 본 세션은 동시 통역이 제공됩니다.

발표자 소개 Simon Chan PredictionIO

Simon is the CEO and co-founder of PredictionIO - an open source Machine Learning Server that empowers programmers and data engineers to build smart applications. Starting off as a software engineer, Simon founded three tech startups in the past 10 years, in the bay area, in Hong Kong and in Mainland China. He specializes in machine learning and recommendation technology, with a strong interest in social applications. Simon holds a B.S.E. in Computer Science from University of Michigan, Ann Arbor and is a PhD candidate in Machine Learning at University College London.

Simon은 프로그래머와 데이터 엔지니어들이 스마트한 어플리케이션을 만드는 데 도움을 줄 오픈소스 머신러닝 서버인 PredictionIO의 공동 창립자이자 CEO입니다. 소프트웨어 엔지니어를 시작한 이후, Simon은 지난 10년간 샌프란시스코와 홍콩, 중국에서 3개의 기술 스타트업을 설립했습니다. 그는 소셜 어플리케이션에 많은 관심을 가지고 있으며, 머신 러닝/추천 기술 전문가입니다. Simon은 미시건대학에서 컴퓨터 과학 학사 학위를 받았고, 유니버시티 칼리지 런던에서 머신 러닝 박사 과정 중에 있습니다.

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