Date/Time:
Location:
Hong Kong Polytechnic University Room BC402
With current technology and the integration of sensing equipment in almost every aspect of our lives (i.e. the IOT - Internet of Things), data collection is ubiquitous. What can be done with all this data? How can it be turned into usable information from which we can derive knowledge? Data Science is the discipline of analysing and making use of this data. In collaboration with KMIRC, KMP's Raymond Ng who has recently completed a year-long study on Data Science will share with us what he has learnt.
The seminar will introduce what data science is and how machine learning can be applied to different kinds of businesses. Some real cases in machine learning will also be explained. This seminar is for those who would consider data science as their future career, or for those who want to apply machine learning to their organization.
Schedule
Agenda for the Data Science Talk on 7 July:
• The age of digitalization
• Data science
• Study for data science
• Machine learning
• Platforms for machine learning
• Real life applications in machine learning
• A real case (DonorsChoose.org)
• Q&A
Speakers
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Raymond Ng Raymond Ng is a practitioner in knowledge management with specializations in both enterprise content management and cultivation of enterprise collaboration. He has more than ten years working experience in the fields of knowledge management and information technology. Over the years, by encouraging and implementing the use of relevant practices and technologies, he has demonstrated the importance of knowledge management and brought positive changes to different organizations and firms. He has led regional projects in implementing content management systems, knowledge bases and social media applications. In academic side, he has a bachelor degree in applied computing and a master degree in knowledge management. In social corporate responsibility side, he is an active participant in helping startups by advising knowledge management practices. |
Organizers
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