EXECUTIVE ML Conference 2017
September 21-22, The Hilton Hotel, Sandton
What is eXe-ML?
Simply put, Executive ML is Machine Learning in practice!
Machine Learning and Artificial Intelligence are finally beginning to surface in the South African market. The purpose of eXe-ML is to bring developing trends in the areas of ML and AI to South Africa and to explore how they are being successfully implemented in industry by leading organizations as solutions to transform and increase productivity. The successful implementation of ML and AI is having a profound impact on industry. eXe-ML will target established and growing South African markets such as retail, finance, security, mining, healthcare, manufacturing, transport, energy and education. You will have the opportunity to hear from local and U.S. speakers about latest developments and applications of ML and AI in these sectors and then, get hands on training on integrating these concepts into your organization.
How is eXe-ML different from other conferences?
Beverly Wright [Georgia Tech]Executive Director, Business Analytics Center, Georgia Institute of Technology
We have selected speakers with experience in the following industries:
Applying ML in practice for real results
Lectures. Networking. Training.
Come and enjoy two full days of Machine Leaning and Artificial Intelligence. On Day 1, experts from both academia and industry will present applications and advances of ML and AI. On Day 2, experienced instructors will show you how to use machine learning in practice with hands on exercises and real data sets.
for more information and inquires contact us
eXe-ML is an educational and networking conference which focuses on practical implementation. You don't need a PhD in science or math to follow this curriculum. After spending a day with us you will not only learn about the trends in ML, but you will learn recipes and lessons that you can immediately apply in your organization. Our speakers are successful professionals who face the same challenges and problems in applying advanced machine learning in their domain. We strongly believe in learning by example and case studies. Learn how to build a data-science team, how to choose software tools, which algorithms to use how to scale your operations, how to communicate your results to your boss and to your clients and how to avoid pitfalls in interpreting your results.