Adam is the CTO of Konduit. Before this, Adam was the cofounder of Skymind. Adam has been using open and producing open source software since 2010 and has been developing machine learning systems since 2012. Adam is a published author and speaker on the field of deep learning on topics ranging from deployment of Production Machine Learning Systems to NLP. Adam grew up in Michigan in the US, spent a few years in Silicon Valley and now resides in Tokyo, Japan.
Yiliang is VP, Head of Data Science with Openspace Ventures, where he is helping OSV’s portfolio companies to be more successful in machine learning and data science operation. He is also teaching applied machine learning courses in NUS and SMU as adjunct faculty. Yiliang has 10+ years of experience in managing and developing end-to-end machine learning projects from ideation to production. He has broad knowledge in predictive modelling, machine learning, natural language processing (NLP) and computer vision (CV). He has solid background in fundamentals of computer science, rich hands-on experience in complete software product development, solid software engineering capabilities and deep understanding of big data system, architecture and optimization. He has extensive experience in driving effective digital transformation using AI/machine learning to derive business insights and make intelligent decisions with quantifiable business impact. Prior to joining OSV, Yiliang was J/APAC Machine Learning Practice Lead with Google Cloud, where he led the ML practice group, oversaw machine learning pipelines and managed training/enablement programs/initiatives in the region. He worked with multinational industry leaders including Fast Retailing, Netmarble, AirAsia, AU Optronics and UOB on various machine learning projects. Yiliang also had extensive experience working in Singapore government as data scientist and tech lead, helping government agencies to solve machine learning and data related problems. Working as a senior data scientist and tech lead at Shopee, Yiliang gained practical understanding of how B2C/C2C ecommerce works in south-east Asia, the related challenges and how data and machine learning can be used to tackle these problems. Yiliang has a Ph.D. in Computer Science from NUS and a B.Eng degree in Computer Engineering from NTU with 1st Class Honours.
MLOps: From Model to Production(Workshop)
Ian Hansel is a Director of Verge Labs, a company empowering businesses through Machine Learning and Artificial Intelligence. Verge Labs bridges the gap between business and cutting-edge research applications. Ian has lead data teams in corporates and believes in taking away the complexity of machine learning to show people how to use amazing technology on their own.
Network Analysis App in Python(Workshop)
Jonathan is on a mission to help businesses generate value through data. As a Senior Data Engineer at Cuusoo (Mantel Group), he empowers organisations with the technology, skills and processes to unleash insights from big data. Outside of his nine-to-five, Jonathan trains and upskills the next generation of data professionals as the Instructor of the Data and Analytics Bootcamp at The University of Western Australia.
Accelerate and broaden your knowledge of key areas in data science, including deep learning, machine learning, and predictive analytics
With numerous introductory level workshops, you get hands-on experience to quickly build up your skills
Post-conference, get access to recorded talks online and learn from over 100+ high quality recording sessions that let you review content at your own pace post conference
Take time out of your busy schedule to accelerate your knowledge on the latest advances in data science practice and management
Learn directly from world-class instructors who are the authors and contributors to many of the tools and languages used in data science today
Get hands-on training in the the tools and woklfow essentatio for MLOps and data engineering.
Network at our numerous lunches and events to meet with data scientists, enthusiasts, and business professionals.
Get access to other focus area content, including machine learning & deep learning, data visualization, and much more
Data scientists moving beyond model experimentation looking to understand production workflow
Data scientists seeking to improve the overall practice of management and development
Anyone interested in understanding better collaborative and agile management techniques as applied to data science
Business professionals and industry experts looking to understand data science in practice
Software engineers and technologists who need to work with data science workflows and understand the unique requirements of these systems
CTO, CDS, and other managerial roles that require a bigger picture view of data science
Technologists in the field of DevOps, databases, project management and others looking to break into data science
Students and academics looking for more practical applied training in data science tools and techniques