Keynote Presentation: How Important will Machine Learning, AI and Deep Learning Applications be for Future Economic Growth?
Discussing the future applications for Machine Learning, and what these may mean for your business – will it live up to the hype? In what ways will these technological changes impact future economic growth and what would the implications be for every day life? With the rise of Artificial Intelligence, what does this mean for… Read more.Speaking
What is the potential of AI, Machine Learning, Algorithms, Natural Language, and Augmented Analytics How far have we come when it comes to adoption and realising the benefits? What are the common use cases? And how can you accelerate adoption in your organisation on a budget?Speaking
Machine learning algorithms aren’t new, but the ability to automatically apply complex mathematical. calculations to big data – over and over, faster and faster – is a recent development. With steady advances in digitisation and cheap computing power, what tangible opportunities does this present for optimising your business and processes? Human vs. Machine – Discussing… Read more.Speaking
Keynote Presentation: Steps for the Successful Implementation of AI/ML: What is AI/ML doing for Your Business Today and How will it Deliver in the Future?
Gain insight on how individuals are leading the way in implementation. Learn how to use ML,DL and AI in practical ways to improve internal efficiencies. Understand how these tools are being used externally to drive profits and better serve their customers.Speaking
Keynote Presentation: How Financial Institutions will Build and Attach Value to Use Cases through Big Data, Analytics and Artificial Intelligence
Analytics Business Value, Artificial Intelligence (AI) vs. Machine learning vs. Deep Learning for Banking use cases. Deriving value in the AI and Analytics journey: from infancy to maturity. The role the Chief Analytics Officer/Head of Advanced Analytics plays in building and Attaching value in a data strategy.Speaking
Best practices in choosing, designing, and implementing from the portfolio of analytical methods including real-time, geospatial, machine learning, statistical, and “big data” Discussing ways to operationalise the results from advanced analytics and models and put them in to action? How do we integrate Internet of Things, pervasive sensing, and the cloud into my companies existing… Read more.Speaking
Analysis of Machine Learning capabilities and how it’s being used. Case studies on the deployment of machine learning. Breaking down siloes and evangelising technological education throughout the whole enterprise to foster innovation.Speaking
Analysing your data management strategy and developing actionable insights. Clarifying the top objectives of your organisation. Establishing touch points in an increasingly digital world. AI/Robotics/ML: How do you use these to create value through customer data in an omnichannel world?Speaking
Should you invest in these new technologies and approaches or not? What is the value, and is it tangible and quantifiable? In a space where innovation outpaces adoption, how can you keep up whilst also increasing trust in the ‘Machine’? What are the barriers to adoption and how can they be overcome?Speaking