LEVERAGING MACHINE LEARNING TO UNLOCK THE VALUE OF DATA TO IMPROVE CUSTOMER ENGAGEMENT, OPERATIONAL EFFICIENCY AND BUSINESS OFFERINGS
Enterprises are entering into a new era of ruled by data and many companies now uses machine learning to identify trends and insights to improve customer engagement, operational efficiency and business offerings.
However, many businesses get stuck in organizing data collection, operationalizing machine learning and translating data into actionable insights for business problems. From re-assessing the value proposition of machine learning to internal stakeholders, getting clean, quality data, defining key factors for success and demonstrating what worked and what didn’t, there is much room to explore and discuss how machine learning can potentially position your business to be competitive real-time.
The inaugural Machine Learning Asia Summit is taking place in Singapore on 26 – 29 March 2018 and will bring together end-users from across industries to share implementation results and demonstrate ways to overcome data challenges.
KEY CONFERENCE THEMES
Machine Learning implementation case studies: Strategies, common pitfalls to avoid and lessons learnt
Getting stakeholders buy-in: Reassess the value proposition of machine learning in the digital age and expedite acceleration of machine learning in your organization with an innovation mindset
Building up data capabilities: Uncover ways on how you can improve your data platform and systems to collect, maintain, manage clean, quality and sufficient data
Demonstrating quantifiable values and outcomes of machine learning: Gain real-world case studies from across BFSI, eCommerce, Real estate industries and more
Improving customer engagement: Uncover how you can enhance customer value and increase your outreach to targeted groups through the right mediums
Vice President, Head of Analytics Centre
Axiata Group Berhad
Head, Allianz Asia Lab (Data Science, Innovation)
Lead Data Scientist
Singapore Exchange Limited
Head of Data Science
Map out your machine learning roadmap from planning to execution and scaling up
Gain practical insights on implementing machine learning – what worked, what didn’t and what to avoid
Knowledge sharing and case-studies from AirAsia, DBS, Surbana Jurong to shed light on machine learning deployment
One-stop gathering of professionals involved in machine learning deployment and dedicated speed networking sessions to help build your network
Interactive discussion groups on top of plenary sessions to get your pressing issues on data challenges addressed